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1
Su, Jiahui, and Yidi Sun. "An Improved TOPSIS Model Based on Cumulative Prospect Theory: Application to ESG Performance Evaluation of State-Owned Mining Enterprises." Sustainability 15, no. 13 (2023): 10046. http://dx.doi.org/10.3390/su151310046.
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The aim of this study is to provide a comprehensive decision-making method that can be applied to investment decisions based on the Environmental, Social and Governance (ESG) performance. The study contributes to the existing literature by introducing the CPT-TOPSIS model, a pioneering approach that incorporates the effect of non-rational factors on decision-making results in uncertain conditions by combining cumulative prospect theory (CPT) with the classic TOPSIS model. Moreover, by conducting an application to ESG evaluation on five state-owned mining enterprises in China, the study provides evidence of the effectiveness and improvement offered by the new model in comparison with the classic TOPSISI model and prospect theory TOPSIS (PT-TOPSIS) model. The results suggest that the CPT-TOPSIS model considers risk preferences and probability distortion in the decision-making process, narrows the gap between ESG scores, and makes ESG performance evaluation more realistic.
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Feng, Dingrong, Zheng Chen, Yanxiong Yang, Ruofeng Qiu, Yunfei Qi, and Tao Liu. "Water Allocation Model Based on Improved TOPSIS Method." Journal of Physics: Conference Series 2333, no. 1 (2022): 012004. http://dx.doi.org/10.1088/1742-6596/2333/1/012004.
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Abstract In this paper, in order to improve traditional TOPSIS water weight distribution model, the analytic hierarchy process combined with coefficient of variation method is used to calculate the weight. In the improved model, vertical distance is adopted to calculate the result, which avoids some defects caused by Euclidean distance. In the process of practical application, improved TOPSIS method selected 12 evaluation indicators with water resources development, social benefits, economic benefits, ecological environmental benefits and other aspects of evaluation, making the model more fit the reality. The results show that when the method is applied to water right allocation in Arizona, the calculated results are in agreement with the practice.
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Huang, Wei Fan. "An Improved TOPSIS Method for Material Selection Model." Advanced Materials Research 951 (May 2014): 120–23. http://dx.doi.org/10.4028/www.scientific.net/amr.951.120.
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Material selection problem becomes an important issue in the material science field. It is important for design for mechanical, electrical, thermal, chemical et al. There are several influencing factors in the material selection process, and thus material selection problem is a multi-criteria decision making (MCDM) problem. Relative entropy measure can depict the closeness of the two systems, and then this paper will use it to develop an improved TOPSIS method for the material selection problem. Finally, a practical example is given to demonstrate that the proposed method is effective and feasible.
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Sun, Xiubo, Changlai Guo, and Jian Cui. "Research on evaluation method of water resources carrying capacity based on improved TOPSIS model." La Houille Blanche, no. 5 (October 2020): 68–74. http://dx.doi.org/10.1051/lhb/2020040.
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Based on the improved TOPSIS model, water resources carrying capacity research is carried out. On the basis of constructing a water resources evaluation index system, the weights are introduced from the traditionally constructed index matrix into the Euclidean distance of the TOPSIS model through subjective and objective weighting. When the ideal solution distance is the same, the larger weighted index corresponds to the greater water resources carrying capacity. The improved TOPSIS model is used to evaluate the water resources carrying. Taking Jinzhou as an example, we determine the advantages of water resources carrying capacity and the influencing factors of the short board in this area. The proposed method has certain theoretical and practical significance.
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Wang, Xia, and Qingquan Duan. "Improved AHP–TOPSIS model for the comprehensive risk evaluation of oil and gas pipelines." Petroleum Science 16, no. 6 (2019): 1479–92. http://dx.doi.org/10.1007/s12182-019-00365-5.
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Abstract A comprehensive and objective risk evaluation model of oil and gas pipelines based on an improved analytic hierarchy process (AHP) and technique for order preference by similarity to an ideal solution (TOPSIS) is established to identify potential hazards in time. First, a barrier model and fault tree analysis are used to establish an index system for oil and gas pipeline risk evaluation on the basis of five important factors: corrosion, external interference, material/construction, natural disasters, and function and operation. Next, the index weight for oil and gas pipeline risk evaluation is computed by applying the improved AHP based on the five-scale method. Then, the TOPSIS of a multi-attribute decision-making theory is studied. The method for determining positive/negative ideal solutions and the normalized equation for benefit/cost indexes is improved to render TOPSIS applicable for the comprehensive risk evaluation of pipelines. The closeness coefficient of oil and gas pipelines is calculated by applying the improved TOPSIS. Finally, the weight and the closeness coefficient are combined to determine the risk level of pipelines. Empirical research using a long-distance pipeline as an example is conducted, and adjustment factors are used to verify the model. Results show that the risk evaluation model of oil and gas pipelines based on the improved AHP–TOPSIS is valuable and feasible. The model comprehensively considers the risk factors of oil and gas pipelines and provides comprehensive, rational, and scientific evaluation results. It represents a new decision-making method for systems engineering in pipeline enterprises and provides a comprehensive understanding of the safety status of oil and gas pipelines. The new system engineering decision-making method is important for preventing oil and gas pipeline accidents.
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Cai, Mei, and Yuanyuan Hong. "Improved TOPSIS Method Considering Fuzziness and Randomness in Multi-Attribute Group Decision Making." Mathematics 10, no. 22 (2022): 4200. http://dx.doi.org/10.3390/math10224200.
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Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a commonly used decision model in multi-attribute group decision making (MAGDM), and a probabilistic linguistic term set (PLTS) is the linguistic variable that can effectively express the fuzziness of decision makers’ (DMs’) preference. However, in actual decision use, PLTS type decision preference needs to be processed before use, which can distort the decision results. The randomness of DM’s preference which also affects the final decision making is often ignored. Therefore, in order to better serve the MAGDM problem, this paper proposes an asymmetric probabilistic linguistic cloud TOPSIS (ASPLC-TOPSIS) method. First, the basic theories of linguistic variables and cloud model (CM) are introduced. Second, the conversation model between linguistic variables and CM is defined along with the operation formula of ASPLC. Third, considering the importance of the DMs’ subjective weights, a DM trust network is established to calculate the DMs’ weights. Finally, the decision process of ASPLC-TOPSIS is proposed and the superiority of this method is proved through experimental studies.
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Liu, Huajian, Hongrui Zhu, and Boyi Yang. "Customer Value Classification Model Based on Improved TOPSIS Method and BP-Adaboost Algorithm." Highlights in Science, Engineering and Technology 115 (October 28, 2024): 277–85. http://dx.doi.org/10.54097/s24sdd38.
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Identifying customer groups with different consumption values can help enterprises understand and analyze customers' purchasing behaviors and preferences, so as to effectively improve their operating profits. In this paper, the customer value evaluation index system is constructed on the basis of existing research on customer value classification using entropy weight method and improved TOPSIS method, and different grades are classified according to the comprehensive score of customers. Subsequently, the customer comprehensive score is used as the output layer, and the BP-Adaboost algorithm is used to construct the customer value classification model. The empirical results show that the improved TOPSIS method is more advantageous in terms of error control and classification accuracy, and the BP-Adaboost algorithm outperforms the traditional BP neural network in the customer value classification model, which improves the classification precision and accuracy. This study provides a powerful tool for dealing with the customer value classification problem, which helps enterprises make more accurate decisions in customer relationship management and resource optimization allocation.
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Meng, Qing Ying, Cai Li Zhang, Ti Song, and Ning Li Li. "The Application of the Improved TOPSIS Method in Bid Evaluation of Highway Construction." Applied Mechanics and Materials 178-181 (May 2012): 1365–68. http://dx.doi.org/10.4028/www.scientific.net/amm.178-181.1365.
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By analysising the disadvantages of the current bid evaluation methods used in highway project,the article builds up TOPSIS model based on coefficient of entropy to evaluating bidding units. First,the weight of each index is calculated by means of entropy weight coefficient method. Then it makes comprehensive assessment about bid evaluation with entropy weight coefficient method and TOPSIS method. The proposed method is applied to evaluating information system integration solutions and satisfactory results are abtained.
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Liu, Linlan, Wei Wang, Guirong Jiang, and Jiang Zhang. "Identifying key node in multi-region opportunistic sensor network based on improved TOPSIS." Computer Science and Information Systems 18, no. 3 (2021): 1041–56. http://dx.doi.org/10.2298/csis200620019l.
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The topology of multi-region opportunistic sensor networks is evolving, and it is difficult to identify the key nodes in the networks by traditional key node identification methods. In this paper, a novel method based on the improved TOPSIS method is proposed to identify the key node from the ferry node. The dynamic topology information is represented by the graph model which is modeled by the temporal reachable graph. Based on the temporal reachable graph, three attributes are constructed to identify the key node, which are average degree, betweenness centrality and message forwarding rate. The game theory with a combination weighting method is employed to combine the subjective weight and objective weight, so as to obtain the combined weight of each attribute. The TOPSIS method is improved by the combined weight. The key node is identified by the improved TOPSIS. The experiments in three simulation situations show that, compared with the TOPSIS method and MADM_TOPSIS method, the proposed method has better accuracy for the key node identification in the network.
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Shuai, Qing Yan, and Ya Bo He. "Application of Improved TOPSIS Method to the Evaluation on Asphalt Pavement Performance." Applied Mechanics and Materials 253-255 (December 2012): 611–15. http://dx.doi.org/10.4028/www.scientific.net/amm.253-255.611.
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As a fundamental work for pavement maintenance management, the evaluation on asphalt pavement performance is the premise of determining the maintenance time and strategy. Aiming at the shortcomings of traditional TOPSIS model, an improved TOPSIS method is proposed to make comprehensive assessment on asphalt pavement performance. Instead of the Euclid distance, the vertical distance between the evaluation object and positive ideal solution is taken as the basis for alternatives ranking. A case study is carried out, indicating that this approach is rational and feasible. The result can provide a certain reference for the road management department to make optimal decision.
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Zhang, Jian, Xianli Zhao, Canmian Liu, and Wei Wang. "Reliability Evolution of Elevators Based on the Rough Set and the Improved TOPSIS Method." Mathematical Problems in Engineering 2018 (July 18, 2018): 1–8. http://dx.doi.org/10.1155/2018/4784965.
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Focusing on reliability evaluation of elevator equipment operation, this paper builds a model for reliability evaluation of elevator equipment. First, we analyze the factors influencing the reliability of elevators and extract the initial evaluation indicators from four macro-perspectives: people, management, equipment, and environment, to build the index system for reliability evaluation of elevator equipment. And, we reduce the indicator set to remove the unnecessary indicators by using the rough set and weight the reduced indicators according to expert opinions. Finally, on this basis, we combine the grey number theory with the TOPSIS method to build an improved TOPSIS evaluation model, to evaluate the reliability of elevators and determine the optimal ordering.
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Li, Zheng, and Yiwen Deng. "Comprehensive evaluation of college students’ engineering entrepreneurship ability based on improved TOPSIS model." Journal of Computational Methods in Sciences and Engineering 24, no. 3 (2024): 2037–47. http://dx.doi.org/10.3233/jcm-230022.
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Marked by artificial intelligence, big data, cloud computing, revolutionary biotechnology, etc., the fourth scientific and technological revolution and industrial revolution are accelerated. In this new situation, China’s higher engineering education is increasingly closely related to the Industrial Revolution, and it is urgent to train new engineering talents with innovation and entrepreneurship abilities, cross-border integration abilities and comprehensive quality to meet the needs of economic and social development. Entrepreneurial engineering talents have become an important force in promoting industrial progress and social development. Training entrepreneurial engineering talents takes engineering practice training as the driving force of teaching reform. To conduct more scientific and effective evaluation research on college students’ engineering entrepreneurship ability, this study proposes the TOPSIS method based on combining CRITIC and entropy weight methods. It constructs a comprehensive evaluation index system of college students’ engineering entrepreneurship ability composed of 21 indexes from four dimensions, including self-motivation ability, team management ability, technical management ability and market management ability. A questionnaire based survey was conducted among 360 college students in 6 Zhejiang Province, China universities. The results show that the improved TOPSIS model proposed in this study can make weight determination more scientific and reasonable. The improved TOPSIS model can effectively distinguish the level of engineering entrepreneurship ability of different college students. The engineering entrepreneurship ability of the students in the six universities is generally at the middle level. The years of engineering education significantly affect technical management ability (F= 4.455, p= 0.004) and market management ability (F= 19.174, p= 0.000) at a 1% level. The research conclusion has important reference value for developing engineering entrepreneurship’s curriculum and practical activity systems based on the ability structure, constructing the entrepreneurship teacher system, and strengthening the cross-departmental cooperation, coordination and integration of engineering entrepreneurship education in schools.
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Liang, Yi, Yingying Fan, Yongfang Peng, and Haigang An. "Smart Grid Project Benefit Evaluation Based on a Hybrid Intelligent Model." Sustainability 14, no. 17 (2022): 10991. http://dx.doi.org/10.3390/su141710991.
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With the accelerated development of smart cities, the construction and development of smart grids have an increasing impact on the safe and stable operation of power systems. The benefit evaluation of smart grids can find out the problems of smart grids more comprehensively, which is of great practical significance for the further development of smart cities. In order to ensure accuracy and real-time evaluation, this paper proposes a new hybrid intelligent evaluation model using an improved technique for order preference by similarity to an ideal solution (TOPSIS) and long–short-term memory (LSTM) optimized by a modified sparrow search algorithm (MSSA). First, a set of smart grid benefit evaluation index systems is established in the context of considering smart city development. Then, aiming at the reverse order problem existing in TOPSIS, an improved evaluation model with entropy weight and modified TOPSIS is established. Finally, an intelligent evaluation model based on LSTM with MSSA optimization is designed. The example analysis verifies the accuracy of the model proposed, points out the important factors affecting the benefits of smart grids, and provides a new idea to achieve effective evaluation and rapid prediction, which can help to improve the benefit level of smart grids.
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Qu, Shengteng, Huan Chen, Zhuge Shen, and Haoxiang Ma. "The performance evaluation of management mode of small water resources projects." PLOS ONE 18, no. 4 (2023): e0282357. http://dx.doi.org/10.1371/journal.pone.0282357.
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Due to a series of societal factors, management of small rural water resources projects in China experience management problems. Based on the management mode of small water resources projects in three representative regions of Guangdong Province, the improved TOPSIS model is applied to evaluate the performance of management mode of small water resources projects through the combination with entropy weight method. Compared with the traditional TOPSIS model concerning the evaluation object of this paper, the evaluation value formulas of optimal and worst solutions of TOPSIS method are improved. The evaluation index system takes into account the coverage, hierarchy and systematization of indicators, and maintains a management mode with high environmental adaptability, so that the continuous operation of management mode can guaranteed. The results show that the management mode of water user association is most suitable for the development of small water resources projects in Guangdong Province.
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Liang, Xuedong, Jinrui Miao, and Qian Lu. "Improved Fuzzy Grey Relational-TOPSIS model for hazardous waste transporter selection." IOP Conference Series: Earth and Environmental Science 467 (April 9, 2020): 012167. http://dx.doi.org/10.1088/1755-1315/467/1/012167.
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Qi, Fangzhong, Leilei Zhang, Kexiang Zhuo, and Xiuyan Ma. "Early Warning for Manufacturing Supply Chain Resilience Based on Improved Grey Prediction Model." Sustainability 14, no. 20 (2022): 13125. http://dx.doi.org/10.3390/su142013125.
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In a dynamic, uncertain environment, increased supply chain resilience can improve business quality. Predicting changes in enterprise supply chain resilience can help enterprises adjust their operational strategy timeously and reduce the risk of supply and demand interruption. First, a comprehensive resilience assessment framework for manufacturing enterprises was constructed from the perspective of the supply chain, and an improved technique for order of preference by similarity to the ideal solution (TOPSIS) method was used to quantify the resilience level. Considering that the resilience index is easily affected by uncertain factors, and this produces large fluctuations, the buffer operator and metabolism idea are introduced to improve the grey prediction model. This improvement can realize dynamic tracking of the enterprise resilience index and evaluate changes in the enterprise resilience level. Finally, through the analysis of the supply chain data of a famous electronic manufacturing enterprise in China over a two-and-a-half-year period, the results show that the improved TOPSIS method and the improved grey prediction model are effective in improving the supply chain resilience of manufacturing enterprises. This study provides a reference method for manufacturing enterprises to improve their supply chain resilience.
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Wang, Wei, Yun Qi, Baoshan Jia, and Youli Yao. "Dynamic prediction model of spontaneous combustion risk in goaf based on improved CRITIC-G2-TOPSIS method and its application." PLOS ONE 16, no. 10 (2021): e0257499. http://dx.doi.org/10.1371/journal.pone.0257499.
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Due to the problems related to the numerous factors affecting the spontaneous combustion of goaf coal, such as sudden, uncertain, and dynamic changes, and the fact that the weight of the indexes in the prediction model of the spontaneous combustion risk is difficult to determine, an improved Criteria Importance Through Inter-criteria Correlation (CRITIC) modified Technique for Order of Preference by Similarity to Ideal Solution G2-(TOPSIS) dynamic prediction model of goaf spontaneous combustion was developed. An optimal decision-making model was established by introducing the Euclidean distance function, and the function-driven type G2 weighting method was modified using the differential-driven type weighting method of the CRITIC. In addition, the comprehensive weights of each index were obtained. An update factor was introduced to obtain the dynamic weight, and the primary-secondary relationship of the risk factors affecting the spontaneous combustion of goaf was evaluated. Based on the G2 weighting method, which approximates the driving function principle of the ideal solution ranking method (TOPSIS), a G2-TOPSIS goaf spontaneous combustion risk assessment model was established. The degree of closeness was analyzed and the risk grade of the goaf spontaneous combustion was finally predicted. The sub-model was applied to the goaf of working face 1303 in the Jinniu Coal Mine. It was concluded that the air leakage duration was the dominant factor inducing the risk of the spontaneous combustion of the goaf. The risk grade of spontaneous combustion of the goaf is Class III, and the predicted results are consistent with the actual situation. The improved CRITIC-G2-TOPSIS dynamic model was demonstrated to be scientific in predicting the goaf spontaneous combustion risk, and these research results have important popularization and application value.
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Zhang, Ying, and Qiang Wang. "The Evaluation of Changsha Urban Ecosystem Sustainable Development Ability Based on Improved TOPSIS Model." Advanced Materials Research 726-731 (August 2013): 5005–13. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.5005.
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Urban ecosystem is a multi-level giant system continuous developing and consist of nature, economy, sociaty and other elements. By adopting the analytic hierarchy process (ahp) this paper established the Changsha urban ecosystem sustainable development indicator system and weight, and used the improved TOPSIS model to evaluate Changsha urban ecosystem development ability.
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Zang, Dongmei, Xinlei Sheng, Liya Wang, Aimin Yang, Tao Xue, and Jie Li. "Research and Application of Warship Multiattribute Threat Assessment Based on Improved TOPSIS Gray Association Analysis." International Journal of Digital Crime and Forensics 14, no. 3 (2022): 1–14. http://dx.doi.org/10.4018/ijdcf.315288.
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Multitarget threat evaluation of warship air attacks is one of the most urgent problems in warship defense operations. To evaluate the target threat quickly and accurately, an air attack multitarget threat evaluation method based on improved TOPSIS gray relational analysis is proposed. This method establishes threat assessment system of five attributes of target type, anti-jamming ability, heading angle, altitude, and speed. The weight coefficient of each index of the warship is obtained by combining the entropy weight method with the analytic hierarchy process. Topsis can make full use of the information of the original data, and its results can accurately reflect the gap between various evaluation schemes. The weighted Mahalanobis distance and comprehensive gray correlation between the attribute to be evaluated and the positive and negative ideal states are calculated by the improved TOPSIS gray correlation method. The target threat degree to be evaluated is obtained by combining the two methods. Finally, an example is given to prove the effectiveness of the evaluation model.
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Chen, Baitong, Xinzhong Bao, and Kun Xu. "Credit Risk Assessment of e-Commerce Supply Chain Finance of SMEs Based on Dynamic Reward and Punishment Perspective." Discrete Dynamics in Nature and Society 2021 (August 30, 2021): 1–9. http://dx.doi.org/10.1155/2021/9702473.
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In view of problems such as lack of dynamism, limited research subjects, and lack of future development trends in previous studies, the paper takes small and microenterprises (SMEs) as research objects under the background of e-commerce supply chain finance. Based on the perspective of dynamic rewards and punishments, credit rewards and punishment value and time weights are embedded in the static evaluation results obtained by the traditional TOPSIS method. The Grey relative analysis method is used to reflect the development trend of enterprises’ credit and to build the traditional TOPSIS model and the credit risk evaluation model of e-commerce supply chain finance of SMEs by the improved TOPSIS method based on the dynamic perspective of rewards and punishments. Finally, the model is applied to SMEs credit risk evaluation of e-commerce supply chain finance to verify the feasibility and rationality of the model.
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Xu, Xizhen, Qun Wang, Xiaoxin Ding, Tiebing Chen, and Ronghui Deng. "Evaluation approach of prefabricated components based on multi-layer complex network model combined with improved topsis method." PLOS One 20, no. 5 (2025): e0322236. https://doi.org/10.1371/journal.pone.0322236.
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Prefabricated buildings face greater and different prefabricated components throughout their entire lifecycle, leading to a significant increase in management difficulty. This article proposes an evaluation method based on a multi-layer complex network model combined with an improved topsis. Firstly, by combining relevant regulations, literature, and engineering experience, the factors affecting the connection of components in prefabricated building are identified and the relationships between these factors are clarified to construct a multi-layered complex network model. Secondly, complex network theory is applied to calculate and analyze the importance evaluation indicators of the model nodes. Finally, the nodes are evaluated using the entropy weight optimization topsis method, and key nodes are selected based on the comprehensive importance evaluation value, and simulation verification is carried out by attacking the nodes. A specific model is constructed and analyzed using a building in Shenzhen, Guangdong Province as an example. The study shows that:(1) By analyzing key importance evaluation metrics such as node degree, betweenness centrality, and closeness centrality, the critical nodes identified for the project are “G2,” “G1,” “S24,” and “Q1”; (2) According to the comprehensive evaluation results using the improved topsis method, quality issues are the core cause of connection problems in prefabricated components, with the construction phase being the peak period for such issues; (3) The critical nodes play a significant role in maintaining the coordination and robustness of multi-layer complex networks, and the failure of these critical nodes undermines the network’s cohesion and synergy. This study provides new insights and methods for the evaluation and management of prefabricated construction.
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Aikhuele, Daniel Osezua, Shahryar Sorooshian, Richard Hannis Ansah, and Faiz Mohd Turan. "Application of Intuitionistic Fuzzy Topsis Model for Troubleshooting an Offshore Patrol Boat Engine." Polish Maritime Research 24, no. 2 (2017): 68–76. http://dx.doi.org/10.1515/pomr-2017-0051.
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Abstract In this paper, an Intuitionistic Fuzzy TOPSIS model which is based on a score function is proposed for detecting the root cause of failure in an Offshore Boat engine, using groups of expert’s opinions. The study which has provided an alternative approach for failure mode identification and analysis in machines, addresses the machine component interaction failures which is a limitation in existing methods. The results from the study show that although early detection of failures in engines is quite difficult to identify due to the dependency of their systems from each other. However, with the Intuitionistic Fuzzy TOPSIS model which is based on an improved score function such faults/failures are easily detected using expert’s based opinions.
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Liu, Shaohui, Nianbai Liang, Jiayang Chen, et al. "Insulation State Assessment of Cable Intermediate Joint based on the Combination of Variable Weight and TOPSIS." Journal of Physics: Conference Series 2424, no. 1 (2023): 012002. http://dx.doi.org/10.1088/1742-6596/2424/1/012002.
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Abstract In order to understand the insulation operation state of cable joint in real time, an evaluation method of cable joint insulation state based on improved TOPSIS with variable weight is proposed. Taking the partial discharge(PD) data monitored online as an example, the representative PD characteristic parameters is selected. Furthermore, Sen + Mann-Kendall test method is used to quantitatively calculate the trend change of corresponding PD characteristic parameters. Then the deterioration degree is introduced to normalize the PD characteristic parameters. Considering the change of weight under extreme deterioration, a variable weight function is constructed to optimize the constant weight. Finally, an improved TOPSIS method is applied to construct the cable intermediate joint state evaluation model. The case analysis shows that this model is more accurately than the traditional model in assessing the insulation condition of cable intermediate joint.
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Yang, Luting, and Yan Li. "A new method for ranking the usefulness of negative online reviews based on combined weighting method and improved TOPSIS." Journal of Intelligent & Fuzzy Systems 42, no. 4 (2022): 3719–36. http://dx.doi.org/10.3233/jifs-211928.
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Online shopping has gradually become an important way of consumption, and consumers are paying more and more attention to negative reviews. In order to avoid the massive amount of negative review information leading to loss of useful information, this paper proposes a method for evaluating the usefulness of negative online reviews. Firstly, the method constructs an evaluation index system for the usefulness of negative online reviews from three aspects: the form feature, text feature, and reviewer feature of negative reviews, and uses a combination weighting method based on fuzzy analytic hierarchy process (FAHP) and entropy method to determine the weight of each index. Secondly, the usefulness ranking results of negative online reviews are obtained through the improved TOPSIS method based on the combined weighting method. Finally, the empirical analysis of the proposed model is carried out by crawling the negative online reviews of JD.com Fresh Food platform, and the improved model is compared with the traditional TOPSIS model, which proves the feasibility and effectiveness of the model.
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Wang, Zeng, Weidong Liu, Minglang Yang, and Dongji Han. "A Multi-Objective Evolutionary Algorithm Model for Product Form Design Based on Improved SPEA2." Applied Sciences 9, no. 14 (2019): 2944. http://dx.doi.org/10.3390/app9142944.
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As a Kansei engineering design expert system, the product form design multi-objective evolutionary algorithm model (PFDMOEAM) contains various methods. Among them, the multi-objective evolutionary algorithm (MOEA) is the key to determine the performance of the model. Due to the deficiency of MOEA, the traditional PFDMOEAM has limited innovation and application value for designers. In this paper, we propose a novel PFDMOEAM with an improved strength Pareto evolutionary algorithm 2 (ISPEA2) as the core and combining the elliptic Fourier analysis (EFA) and the entropy weight and technique for order preference by similarity to ideal solution (entropy-TOPSIS) methods. Based on the improvement of the original operators in SPEA2 and the introduction of a new operator, ISPEA2 outperforms SPEA2 in convergence and diversity simultaneously. The proposed model takes full advantage of this superiority, and further combines the EFA method’s high accuracy and degree of multi-method integration, as well as the entropy-TOPSIS method’s good objectivity and operability, so it has excellent comprehensive performance and innovative application value. The feasibility and effectiveness of the model are verified by a case study of a car form design. The simulation system of the model is developed, and the simulation results demonstrate that the model can provide a universal and effective tool for designers to carry out multi-objective evolutionary design of product form.
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Yang, Zhe, Kan Yang, Yufeng Wang, Lyuwen Su, and Hu Hu. "The improved multi-criteria decision-making model for multi-objective operation in a complex reservoir system." Journal of Hydroinformatics 21, no. 5 (2019): 851–74. http://dx.doi.org/10.2166/hydro.2019.150.
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Abstract In multi-objective reservoir operation, it is vital for decision-makers to select optimal scheduling schemes through efficient multi-criteria decision-making (MCDM) techniques. However, in the family of MCDM methods, it is difficult for the technique for order preference by similarity to an ideal solution (TOPSIS) to describe grey correlation, thus making decisions with less reliability. To this end, a framework supporting high-quality solutions' acquirement and optimal reservoir operation decision-making is established. The improved multi-objective particle swarm optimization (IMOPSO), a new efficient MCDM model based on TOPSIS and grey correlation analysis (GCA), and combination weighting method based on the minimum deviation (CWMMD) are included in the framework. The non-inferior solution set is efficiently obtained by IMOPSO and optimal decision information is provided for decision-makers using the MCDM model. Moreover, the CWMMD is used to determine weighting information of multiple evaluation indicators. Numerical simulations are conducted to verify the efficiency of the proposed methodology and support decision-making for multi-objective reservoir operation in Hongjiadu and Qingjiang basins. The results indicate that the proposed methodology can provide non-inferior scheduling solutions and decision-making instruction with higher reliability for multi-objective reservoir operation.
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Lu, Haonan, Yongman Zhao, Xue Zhou, and Zikai Wei. "Selection of Agricultural Machinery Based on Improved CRITIC-Entropy Weight and GRA-TOPSIS Method." Processes 10, no. 2 (2022): 266. http://dx.doi.org/10.3390/pr10020266.
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In view of the problems existing in the process of agricultural machinery selection, such as inadequate decision-making information, strong subjectivity and quantification difficulty of the index weight assignment, and accuracy deficiency of the selection results, a model on the selection of agricultural machinery based on the improved CRITIC-entropy weight and GRA-TOPSIS method was established in this study. Through analysis, based on the construction of a comprehensive evaluation index system for the selection of agricultural machinery, the combined weight value was determined by combining the weights obtained using the improved CRITIC method and the weights obtained using the entropy weight method. The grey relational analysis method was also combined with the TOPSIS method. The power machinery combination with 88.2 and 73.5 kW of the 68th Regiment of the Fourth Division of Xinjiang Production and Construction Corps was used as an example for verification to determine the optimal power machinery combination. Results indicated that the ranking results were consistent, and the GRA-TOPSIS method was of the greatest degree of discrimination, which was conducive to the selection and evaluation of agricultural machinery equipment. Moreover, the equipment selection results were determined after the comprehensive ranking of machinery types under the different subjective preferences of decision makers was performed.
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Xue, Xinxin. "Research on the Evaluation of Water Resources Carrying Capacity in the Central Plains Urban Agglomeration Based on the PS-DR-DP Model." Engineering and Technology Journal 9, no. 08 (2024): 4898–906. https://doi.org/10.5281/zenodo.13373178.
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Adequate Water Resource Carrying Capacity (WRCC) is of great significance for the sustainable development of urban agglomerations. Accurately evaluating WRCC is of great significance for the coordinated development of urban agglomerations. Based on the PS-DR-DP framework, an evaluation index system for water resources carrying capacity was established, and the main obstacle factors affecting CPUA WRCC were analyzed using an obstacle degree model. The WRCC index of the Central Plains Urban Agglomeration (CPUA) was calculated using the Improved TOPSIS model, and the evolution and spatial distribution characteristics of WRCC were analyzed. The results indicate that the water resources carrying capacity of the Central Plains urban agglomeration has been coordinated and sustainable in recent years.
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Wen, Hao, Liu Shi, Yakun Wang, and Ting Ni. "Layout Scheme Comparison of the Switching Station of Guoduo Hydroelectric Project Based on AHP-TOPSIS." E3S Web of Conferences 385 (2023): 03004. http://dx.doi.org/10.1051/e3sconf/202338503004.
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The combination of AHP and TOPSIS can make the evaluation method easy to operate, and improve the objectivity and accuracy of the results. The mathematical model for the switching station scheme optimization was set up to choose an appropriate layout for the Guoduo hydropower station. Through the field survey and literature review, the expert questionnaire was finished. The weights of the index were calculated using the AHP method. Then the improved TOPSIS was employed for the index standardization and the sequencing calculation. The final option of layout 2 was obtained.
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Wei, Chao, Xiaoyan Dai, Yiyou Guo, Xiaohua Tong, and Jianping Wu. "An Improved Approach of Integrated Carrying Capacity Prediction Based on TOPSIS-SPA." Sustainability 14, no. 7 (2022): 4051. http://dx.doi.org/10.3390/su14074051.
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Regional coordinated development is an important policy to promote socio-economic development, especially in the Yangtze River Delta, Greater Bay Area and others, which is one of the guidelines of the 14th Five-Year Plan for economic development. The relative stability of the carrying capacity (CC) is the precondition for long-term rapid development, whereas the comprehensive capacity of natural resources, ecological environment, social economy, population and others, defined as integrated carrying capacity (ICC). Due to the complexity of the CC quantitative assessment, constructing an accurate ICC predication model is the core challenge of dynamic adjustments of socio-economic development planning. In this study, four critical issues, which focused on indicator value estimation, optimal ICC value screening, ICC tendency prediction and study area application in order to formulate a novel prediction framework, are investigated as follows: (1) The proposal formulated an estimation model of indicator value in the future based on the grey model. The grade ratio and the relative residuals of all third-class indicators are less than 0.1, which is highly accurate for indicator value estimation. (2) The optimal ICC value screening model was proposed based on the multi-objective decision-making theory. The optimal ICC values of Suzhou, Ningbo and Zhoushan were 0.7002, 0.6797 and 0.5982, which were also the maximum values from 1996 to 2019. However, the values of Nantong, Jiaxing and Shaoxing were recorded in 2018, 2001 and 1999, which were not the maximum ICC values, and the difference ratio was more than 10%. The optimal ICC value of these three cities were improved. (3) The ICC prediction model was constructed based on the theory of set pair analysis and Euclidean distance. The ICC prediction result of eight cities maintained a relative fluctuation during 2020–2030. Compared with the polynomial fitting curve predication, there were some differences in Nantong, Shaoxing and Zhoushan over the next 5 years. This study provided an improved approach of ICC prediction model, focusing on indicator weight, indicator data estimation and optimal ICC value screening. The model and conclusion aim to validate the rationality of economic planning target for government policymakers and stakeholders.
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Tong, Kun, and Chao Yang. "The Grain Security Assessment Based on Improved TOPSIS Model in Yunnan Province China." International Journal of Food Science and Biotechnology 4, no. 3 (2019): 56. http://dx.doi.org/10.11648/j.ijfsb.20190403.11.
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Wang, Yongli, Xiangyi Zhou, Hao Liu, et al. "Evaluation of the Maturity of Urban Energy Internet Development Based on AHP-Entropy Weight Method and Improved TOPSIS." Energies 16, no. 13 (2023): 5151. http://dx.doi.org/10.3390/en16135151.
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With the rapid development of communication technology and information processing technology, the construction of the Urban Energy Internet (UEI) has become one of the important construction elements of the new power system, and it is necessary to assess and analyse its development status and potential. However, the results of the current assessment of the maturity of UEI development are relatively rare, and the transformation path of urban smart energy construction needs to be studied in depth. On this basis, this study aims to propose an improved and comprehensive evaluation model for the maturity of UEI development. This study first considers the dynamic development process of the UEI and proposes an evaluation index system for the maturity of UEI development that includes three dimensions of development status, development benefits and development prospects. Secondly, a comprehensive evaluation model based on GRA-KL-TOPSIS is constructed by using the AHP-entropy weighting method to calculate the combined weights of indicators and considering the Kulla back-Leibler distance to replace the Euclidean distance in the traditional evaluation method. Finally, the maturity of Energy Internet development is calculated for five typical first-tier cities in China (Beijing, Shanghai, Guangzhou, Tianjin and Shenyang), and the final ranking of the five cities is Shanghai > Beijing > Guangzhou > Tianjin > Shenyang. The results of the study prove the scientific validity of the model. Compared to the unimproved Topsis method, the evaluation results calculated based on the improved Topsis evaluation model are more objective and realistic in reflecting the score and rating of the cities. The analysis of the empirical results shows that cities at different stages of development should make up for their shortcomings and increase their investment in infrastructure development, technological innovation and the introduction of talents in order to accelerate the digital and intelligent development of energy.
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Pang, Bo, Shulan Shi, Gang Zhao, Rong Shi, Dingzhi Peng, and Zhongfan Zhu. "Uncertainty Assessment of Urban Hydrological Modelling from a Multiple Objective Perspective." Water 12, no. 5 (2020): 1393. http://dx.doi.org/10.3390/w12051393.
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The uncertainty assessment of urban hydrological models is important for understanding the reliability of the simulated results. To satisfy the demand for urban flood management, we assessed the uncertainty of urban hydrological models from a multiple-objective perspective. A multiple-criteria decision analysis method, namely, the Generalized Likelihood Uncertainty Estimation-Technique for Order Preference by Similarity to Ideal Solution (GLUE-TOPSIS) was proposed, wherein TOPSIS was adopted to measure the likelihood within the GLUE framework. Four criteria describing different urban stormwater characteristics were combined to test the acceptability of the parameter sets. The TOPSIS was used to calculate the aggregate employed in the calculation of the aggregate likelihood value. The proposed method was implemented in the Storm Water Management Model (SWMM), which was applied to the Dahongmen catchment in Beijing, China. The SWMM model was calibrated and validated based on the three and two flood events respectively downstream of the Dahongmen catchment. The results showed that the GLUE-TOPSIS provided a more precise uncertainty boundary compared with the single-objective GLUE method. The band widths were reduced by 7.30 m3/s in the calibration period, and by 7.56 m3/s in the validation period. The coverages increased by 20.3% in the calibration period, and by 3.2% in the validation period. The median estimates improved, with an increase of the Nash–Sutcliffe efficiency coefficients by 1.6% in the calibration period, and by 10.0% in the validation period. We conclude that the proposed GLUE-TOPSIS is a valid approach to assess the uncertainty of urban hydrological model from a multiple objective perspective, thereby improving the reliability of model results in urban catchment.
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Li, Hongxia, Lei Chen, Fangyuan Tian, Lin Zhao, and Shuicheng Tian. "Comprehensive Evaluation Model of Coal Mine Safety under the Combination of Game Theory and TOPSIS." Mathematical Problems in Engineering 2022 (October 14, 2022): 1–15. http://dx.doi.org/10.1155/2022/5623282.
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At present, the frequent occurrence of coal mine accidents in China is a key concern in the field of safety. Although the coal mine accident rate is decreasing due to the progress of technology and the improvement of management, there is still a lack of comprehensive evaluation of the role of various factors in the coal mine. Therefore, the purpose of this study is to establish a game theory combination weight-TOPSIS comprehensive evaluation model based on the analysis of various factors affecting coal mine safety. The model combines the weights obtained from fuzzy analytic hierarchy process (FAHP), entropy weight method (EWM), and back propagation neural network (BP-NN) by using the combination method of game theory and then combines with the TOPSIS method to evaluate 20 indicators in four aspects of a coal mine: personnel, equipment, environment, and management. Taking five mines under Zheng Coal Group as an example, the evaluation results of the game theory combination weight-TOPSIS comprehensive evaluation model are compared with those of the fuzzy analytic hierarchy process and the improved composite weight-TOPSIS method. The results show that the safety grade of the five mine samples under Zhengmei Group is ranked as follows: mine 4 > grade II (relatively safe) > mine 2 > mine 5 > grade III (moderately safe) > mine 3 > mine 1 > grade IV (generally safe). The evaluation result of the game theory combination weight-TOPSIS method is basically consistent with the actual safety situation of the coal mine, which reflects the superiority and practicality of the evaluation model. The model has greater differentiation in the process of determining the coal mine safety grade, and the evaluation results are more intuitive and reasonable, which can provide a more effective evaluation tool for the comprehensive evaluation of coal mine safety. Finally, based on the evaluation results, corresponding policy recommendations to improve the status quo of coal mine safety are proposed, aiming to provide decision-making reference for coal mine safety management personnel.
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Zhao, Pengfei, Lingxiang Wei, Dong Pan, and Shuai Dong. "Multicriteria Model for Shared Parking and Parking Route Recommender Systems." Journal of Advanced Transportation 2022 (August 29, 2022): 1–17. http://dx.doi.org/10.1155/2022/8369362.
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In many congested areas, shared parking has gotten increasing attention because of its potential to alleviate parking resource shortages. However, managing parking resources remains a challenge when simultaneously considering multiple decision-making criteria of public travelers in allocating parking spaces and recommending optimal parking routes. To fill this gap, from four perspectives, i.e., driving, among shared parking lots, at a shared parking lot, between shared parking spaces and destinations, we proposed nine criteria for shared parking space allocations and parking route recommendations, and we also gave the quantitative models for different criteria. Furthermore, an analytic hierarchy process Entropy-TOPSIS grey relational analysis (AHP-Entropy-TOPSIS-GRA) method and an improved ant colony algorithm were proposed to solve the proposed allocation of parking spaces and recommend optimal parking routes, respectively. Finally, the validity of our proposed models and algorithms was tested by empirical parking data and road traffic data collected in Huai’an City, Jiangsu province, China. The research helps provide a theoretical foundation for implementing shared parking initiatives and improving public travelers’ parking satisfaction.
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Liu, Jianfen, and Shengpu Li. "Research on the Ranking of University Education based on Grey-TOPSIS-DEA Method." International Journal of Emerging Technologies in Learning (iJET) 10, no. 8 (2015): 51. http://dx.doi.org/10.3991/ijet.v10i8.5279.
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The University is the cradle of the higher education. In the college life, the college students continue to accept the new knowledge and continue to grow. Obviously, the level of the university education will be directly related to the growth for the college students. Therefore, it is an important job to evaluate and order the college education quality. In this paper, we combine the Grey theory, TOPSIS with DEA method. And we propose an improved Grey-TOPSIS-DEA model. Then, we use the model to evaluate the college education quality. Finally, we get the rankings of the college education. In the last part of this paper, we use the method to evaluate the education quality for different colleges. And we verify the validity of the method.
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Xing, Yitian, Fue-Sang Lien, William Melek, and Eugene Yee. "A Multi-Hour Ahead Wind Power Forecasting System Based on a WRF-TOPSIS-ANFIS Model." Energies 15, no. 15 (2022): 5472. http://dx.doi.org/10.3390/en15155472.
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Wind is a renewable and green energy source that is vital for sustainable human development. Wind variability implies that wind power is random, intermittent, and volatile. For the reliable, stable, and secure operation of an electrical grid incorporating wind power systems, a multi-hour ahead wind power forecasting system comprising a physics-based model, a multi-criteria decision making scheme, and two artificial intelligence models was proposed. Specifically, a Weather Research and Forecasting (WRF) model was used to produce wind speed forecasts. A technique for order of preference by similarity to ideal solution (TOPSIS) scheme was employed to construct a 5-in-1 (ensemble) WRF model relying on 1334 initial ensemble members. Two adaptive neuro-fuzzy inference system (ANFIS) models were utilised to correct the wind speed forecasts and determine a power curve model converting the improved wind speed forecasts to wind power forecasts. Moreover, three common statistics-based forecasting models were chosen as references for comparing their predictive performance with that of the proposed WRF-TOPSIS-ANFIS model. Using a set of historical wind data obtained from a wind farm in China, the WRF-TOPSIS-ANFIS model was shown to provide good wind speed and power forecasts for 30-min to 24-h time horizons. This paper demonstrates that the novel forecasting system has excellent predictive performance and is of practical relevance.
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Jahan, A., M. Yazdani, and K. L. Edwards. "TOPSIS-RTCID for range target-based criteria and interval data." International Journal of Production Management and Engineering 9, no. 1 (2021): 1. http://dx.doi.org/10.4995/ijpme.2021.13323.
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<p>The Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) is receiving considerable attention as an essential decision analysis technique and becoming a leading method. This paper describes a new version of TOPSIS with interval data and capability to deal with all types of criteria. An improved structure of the TOPSIS is presented to deal with high uncertainty in engineering and engineering decision-making. The proposed Range Target-based Criteria and Interval Data model of TOPSIS (TOPSIS-RTCID) achieves the core contribution in decision making theories through a distinct normalization formula for cost and benefits criteria in scale of point and range target-based values. It is important to notice a very interesting property of the proposed normalization formula being opposite to the usual one. This property can explain why the rank reversal problem is limited. The applicability of the proposed TOPSIS-RTCID method is examined with several empirical litreture’s examples with comparisons, sensitivity analysis, and simulation. The authors have developed a new tool with more efficient, reliable and robust outcomes compared to that from other available tools. The complexity of an engineering design decision problem can be resolved through the development of a well-structured decision making method with multiple attributes. Various decision approches developed for engineering design have neglected elements that should have been taken into account. Through this study, engineering design problems can be resolved with greater reliability and confidence.</p>
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Alahmadi, Oudah Ali Oudah. "Development of a Risk Assessment and Management Model for UNESCO World Heritage Site." International Journal of Advanced Engineering Research and Applications 8, no. 03 (2022): 104–12. http://dx.doi.org/10.46593/ijaera.2022.v08i03.001.
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Historical Location propose wide range of risks that can impact reptation, assets, or people that can have major impact. There for Risk management plans was improved in At-Turaif to cope with hazards. The objective of the study is to develop a risk assessment and find which building has the highest priority. The rank will be conducted using MCDM (Multi-Criteria Decision-Making) using five criteria (1) Risk rate, (2) Heritage value, (3) Important, (4) maximum occupancy, and (5) Traffic. These five criteria were applied through AHP-TOPSIS to find the highest rank building. The result of the risk assessments indicates there are electric, physical, fire, environmental, and security hazards. Risk assessment also propose control plan for each hazard. Based on AHP-TOPSIS results. All 28 buildings were rank according to the five criteria with Salwa palace, traditional homes, Omar palace, and Beit Almal need to be prioritized due to their important according to TOPSIS results. Some souks and Clusters fall in the lower section of the rank due to it risk rate and heritage value. The study recommends conducting further research on mud buildings and heritage sites in Saudi Arabia, as it is unique for the country, and recommends plans to eliminates the main hazards such as mud damages by spraying walls with protective coating. And develop new SOP (Standard operation procedures) for the worker to follow. Additionally, the study recommends improving the hazards control strategy and implement new action for hazards.
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Oliveira, Altina S., Carlos F. S. Gomes, Camilla T. Clarkson, et al. "Multiple Criteria Decision Making and Prospective Scenarios Model for Selection of Companies to Be Incubated." Algorithms 14, no. 4 (2021): 111. http://dx.doi.org/10.3390/a14040111.
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This paper proposes a model to evaluate business projects to get into an incubator, allowing to rank them in order of selection priority. The model combines the Momentum method to build prospective scenarios and the AHP-TOPSIS-2N Multiple Criteria Decision Making (MCDM) method to rank the alternatives. Six business projects were evaluated to be incubated. The Momentum method made it possible for us to create an initial core of criteria for the evaluation of incubation projects. The AHP-TOPSIS-2N method supported the decision to choose the company to be incubated by ranking the alternatives in order of relevance. Our evaluation model has improved the existing models used by incubators. This model can be used and/or adapted by any incubator to evaluate the business projects to be incubated. The set of criteria for the evaluation of incubation projects is original and the use of prospective scenarios with an MCDM method to evaluate companies to be incubated does not exist in the literature.
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Biglari, Sohrab, Zadollah Fathi, and Mir feiz Fallahshams Layalestani. "Design and Explanation of Portfolio Optimization Model Using Similarity and TOPSIS Methods." Management Strategies and Engineering Sciences 6, no. 1 (2024): 64–70. https://doi.org/10.61838/msesj.6.1.7.
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This study examines and optimizes investment portfolios using Similarity and TOPSIS methods. The aim of this study is to identify and rank assets in order to create a diversified and low-risk portfolio that can provide the best possible returns. The Similarity method is used to identify the correlation between assets and find more diversified combinations, while the TOPSIS method ranks assets based on their proximity to the positive ideal by evaluating multiple criteria. This research is applied in nature and is classified as descriptive-survey research in terms of data collection method. The statistical population of the study includes companies listed on the stock exchange during the period from 2011 to 2020. A judgmental sampling method is employed in this research. The results indicate that the combination of these two methods with the Markowitz model can lead to improved portfolio performance and offer better results under different market conditions. This practical approach enables investors to create an optimized portfolio resistant to market fluctuations through detailed analysis based on multiple data points.
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Jiang, Wangxi, Xiaoxiong Wu, Mingyang Song, Jiwei Qin, and Zhenhong Jia. "Improved PBFT Algorithm Based on Comprehensive Evaluation Model." Applied Sciences 13, no. 2 (2023): 1117. http://dx.doi.org/10.3390/app13021117.
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Blockchain technology is well known due to the advent of Bitcoin. With the development of recent years, blockchain technology has been widely used in medicine, digital currency, energy, etc. The practical Byzantine fault-tolerant (PBFT) algorithm is a consensus algorithm widely used in consortium blockchains. Aiming to address the problems of the PBFT algorithm, low consensus efficiency due to high communication complexity, and malicious behavior of the primary node leading to consensus failure, an improved PBFT algorithm based on a comprehensive evaluation model (TB-PBFT) is proposed. First, nodes are divided into several groups based on the multi-formation control strategy of an unmanned aerial vehicle (UAV) cluster, which significantly reduces the communication complexity. Second, a comprehensive evaluation model combining the entropy method, TOPSIS method, and Borda count is proposed, which uses the behavior of nodes as an evaluation index, and the comprehensive score of nodes is obtained according to the preferences of other nodes. Finally, the highest ranking node is selected as the primary node through the comprehensive evaluation model to ensure the security and stability of the blockchain network. We analyze TB-PBFT algorithms and compare them with other Byzantine fault tolerance algorithms. Theoretical analysis and simulation results show that the TB-PBFT algorithm can improve node scalability and fault tolerance and reduce communication complexity and view switching probability. We also prove that the comprehensive evaluation model can improve the consensus success rate of the algorithm, and the feasibility and effectiveness of the improved consensus algorithm are verified. Hence, it can be applied to the consortium blockchain system effectively and efficiently.
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Ding, Keyuan, and Ruoyu Yang. "Application of Delphi-Entropy Weight-TOPSIS Model in the Assessment of Safe Urban Development." Journal of Combinatorial Mathematics and Combinatorial Computing 127a (April 15, 2025): 2639–55. https://doi.org/10.61091/jcmcc127a-149.
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Urban safety development is one of the guarantees for the overall development of the city, and the study uses Delphi method, entropy weight method and TOPSIS method in the assessment of urban safety development. An improved Delphi-entropy weight-TOPSIS combination assessment model is constructed to evaluate the urban safety development. The evaluation index system of urban safety development is constructed, and the evaluation indexes of urban safety development are calculated by Delphi method and entropy weight method respectively, and the subjective and objective weights of the evaluation indexes of urban safety development are derived, and finally, the comprehensive weights are calculated by the method of combined weight assignment. The comprehensive weights of the guideline layer of the urban safety development evaluation index system are 0.1874, 0.2080, 0.2005, 0.2187, and 0.1854, respectively.The evaluation index system is used for empirical research, and City A is taken as the object of the research to assess its urban safety development status during the 10-year period from 2014 to 2023. From the evaluation results, it is known that the overall urban safety development of City A during the 10-year period shows an upward trend, with slight fluctuations in the process, but the overall development is good, and the evaluation score of urban safety development improves from 0.4657 points in 2014 to 0.6479 points in 2023.
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Wang, Wen, and Bo Yang. "Dynamic evaluation of water resource carrying capacity in Hainan Island based on improved TOPSIS model." E3S Web of Conferences 603 (2025): 04008. https://doi.org/10.1051/e3sconf/202560304008.
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Introducing a GIS based analysis matrix of inherent condition indicators and grading standards for engineering water supply, an improved TOPSIS model was used to evaluate the water resource carrying capacity of 17 cities and counties on Hainan Island. The results show a poor evaluation level of water resource carrying capacity in most cities and counties. There is a weakness of water supply capacity, as well as a high level of demand pressure for water resources. The main limiting factors for cities and counties with a rating of "Poor" are reflected in water use efficiency indicators. The water resource carrying capacity of the central and southern regions is better than that of the northeast region.
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Wang, Weixia, and He Jun. "Application of TOPSIS Method Based on Entropy Weight -Delphi in the Evaluation of Teachers’ “double-qualified” Ability." E3S Web of Conferences 165 (2020): 06050. http://dx.doi.org/10.1051/e3sconf/202016506050.
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In order to improve the rationality and fairness of Teachers’ “Double-qualified” Ability, the article establishes an evaluation model based on 14 evaluation indexes of teachers’ “double-qualified” ability. it adopts Delphi - entropy weight method to weight the evaluation index, and then combines TOPSIS method to evaluate the evaluation object. In the evaluation of TOPSIS method, the traditional TOPSIS weight method was improved, and the entropy weight-delphi method was used to determine the index weight, which was a combination of subjective and objective, making the evaluation system more objective, scientific and reasonable.It not only avoids the subjectivity of decision makers and limitations, but also eliminates the phenomenon of indexes in common impact assessment results and finally applies it to a university teacher “Double division and triple energy” evaluation system, to provide theoretical basis and feasibility analysis for the “double type” teachers team construction. Chinese library classification number: O224 Document identification code: A
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Wang, Liang, Runtong Zhang, and Huan Ruan. "A Personalized Recommendation Model in E Commerce Based on TOPSIS Algorithm." Journal of Electronic Commerce in Organizations 12, no. 2 (2014): 89–100. http://dx.doi.org/10.4018/jeco.2014040107.
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From the perspective of performance and universality, this paper analyzed the characteristics of typical technologies for personalized recommendation system, and then made a basic architecture for the improved model. With the architecture, this paper introduced a personalized recommendation model in e-commerce system. The model is based on an n-tiers structure and the TOPSIS algorithm, first standardize the user evaluation indexes, and then determine the indexes weights according to user's needs, and finally calculate the personalized recommendation results. This model can be applied to a variety of e-commerce applications, especially for the e-commerce application with structured or semi-structured products such as digital books, journals and other publications.
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Lou, Xi Juan. "Dynamic Multi-Attribute Decision Making Model with the Area Closeness Degree." Applied Mechanics and Materials 321-324 (June 2013): 2557–60. http://dx.doi.org/10.4028/www.scientific.net/amm.321-324.2557.
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The aim of this paper is to explore dynamic multi-attribute decision making (DMADM) problems in which the decision making information of alternatives is collected at different stages. Firstly, the area closeness degree is applied in normalizing the raw data. Secondly, the weights of different stages are determined by according to the principle of new information priority. The technique for preference by similarity to ideal solution (TOPSIS) is improved to aggregate the information from different stages. Finally, the example is illustrated to demonstrate the practicality and effectiveness of the proposed methods.
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Song, Jing, and Junhui Zheng. "The Application of Grey-TOPSIS Method on Teaching Quality Evaluation of the Higher Education." International Journal of Emerging Technologies in Learning (iJET) 10, no. 8 (2015): 42. http://dx.doi.org/10.3991/ijet.v10i8.5219.
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The teaching quality of the higher school is not only related to the development of the students, but also related to the future of our country. It can find out the problems of the higher education for colleges to evaluate the teaching quality of the higher education. And it can provide the reference for the students to apply for the colleges. In this paper, we combine the grey correlation with TOPSIS method and provide the improved Grey-TOPSIS method. Then, we evaluate the teaching quality of the higher education. The results show that the comprehensive evaluation model can evaluate reasonably the teaching quality of the higher education. And it proves the validity and reliability of the method.
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Liu, Longhui, Yang Zhou, Qing Xu, Qunshan Shi, and Xiaofei Hu. "Improved technique for order of preference by similarity to ideal solution method for identifying key terrain in cyberspace asset layer." PLOS ONE 18, no. 7 (2023): e0288293. http://dx.doi.org/10.1371/journal.pone.0288293.
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Reinforcing weak cyberspace assets is an urgent requirement to defend national cybersecurity. Cyberspace key terrain (CKT) is a theory recently proposed for sensing cyberspace posture. Identifying CKT in the asset layer is essential for supporting cyberspace defense decisions. Existing methods ignore the influence of the multi-attribute correlation of cyberspace nodes and cyber attack mission (CAM) diversity, which restricts the recognition accuracy of CKT. To improve the accuracy of CKT identification and explore the relationship between CKT and CAM, we propose an improved cosine similarity technique for order of preference by similarity to the ideal solution (CosS-TOPSIS) method to model CKT and construct a CAM based on the MITRE adversarial tactics, techniques, and common knowledge (ATT&CK) framework to examine the influence of different weighted CAM on modeling CKT. Based on the vulnerability value calculation method of the cyber system in the common vulnerability scoring system version 3.1 (CVSS 3.1), we evaluated the effectiveness of CosS-TOPSIS in identifying CKT using three metrics: correlation coefficient, root mean square error, and mean absolute error. Our experiments showed that, in comparison with the TOPSIS method, the accuracy of the proposed method for identifying CKT improved by 8.9%, and the root mean square error reduced by 16%; simultaneously, CAM was proven to be an essential factor in identifying CKT. The feasibility and reliability of CosS-TOPSIS in identifying CKT and the close relationship between CAM and CKT identification were demonstrated experimentally. In our work, we utilized cosine similarity and FAHP to improve the baseline method. We also introduced three indicators to evaluate the method’s reliability. Drawing from ATT&CK, we recommend CAM as a tool for sensing changes in the cyberspace environment and explore its relationship with CKT. Our work has great application potential for identifying cyberspace vulnerabilities, supporting cyberspace defense, and securing national cyberspace facilities.
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Wu, Han, Junwu Wang, Jingtao Feng, Denghui Liu, and Sen Liu. "Research on the decision-making of flood prevention emergency plans during reservoir construction based on generalized intuitionistic fuzzy soft sets and TOPSIS." Water Supply 20, no. 8 (2020): 3665–75. http://dx.doi.org/10.2166/ws.2020.182.
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Abstract Reservoir engineering is of great significance for the reduction of regional flood disasters and ensuring the sustainable development of agriculture. This paper proposed a decision-making model based on generalized intuitionistic fuzzy soft sets and TOPSIS. First, an evaluation index system was comprehensively identified and constructed. Then, generalized intuitionistic fuzzy soft sets were used to describe the index attribute values of emergency plans to fully reflect the certainty, uncertainty, and hesitancy of indexes, and their weights were calculated by Fuzzy Ordered Weighted Averaging (FOWA) to adequately consider the ambiguity of experts' judgment. Finally, the TOPSIS method was extended via the generalized intuitionistic fuzzy soft sets to the sequencing of emergency plans. In addition, the Wangjiazhou Reservoir Project in China was selected as a case study. The case study demonstrated that full use of emergency materials and personnel was the most important factor, and the plan of the overflow rock-fill dam was the optimal flood prevention emergency plan. Compared with the classical TOPSIS, the new model proposed in this paper was found to have improved feasibility and effectiveness, and its evaluation results were more objective and reasonable. Therefore, the proposed method could provide both theoretical and practical reference.