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Quan, Huafeng, Shaobo Li, Hongjing Wei, and Jianjun Hu. "Personalized Product Evaluation Based on GRA-TOPSIS and Kansei Engineering." Symmetry 11, no. 7 (2019): 867. http://dx.doi.org/10.3390/sym11070867.
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With the improvement of human living standards, users’ requirements have changed from function to emotion. Helping users pick out the most suitable product based on their subjective requirements is of great importance for enterprises. This paper proposes a Kansei engineering-based grey relational analysis and techniques for order preference by similarity to ideal solution (KE-GAR-TOPSIS) method to make a subjective user personalized ranking of alternative products. The KE-GRA-TOPSIS method integrates five methods, including Kansei Engineering (KE), analytic hierarchy process (AHP), entropy, game theory, and grey relational analysis-TOPSIS (GRA-TOPSIS). First, an evaluation system is established by KE and AHP. Second, we define a matrix variate—Kansei decision matrix (KDM)—to describe the satisfaction of user requirements. Third, the AHP is used to obtain subjective weight. Next, the entropy method is employed to obtain objective weights by taking the KDM as input. Then the two types of weights are optimized using game theory to obtain the comprehensive weights. Finally, the GRA-TOPSIS method takes the comprehensive weights and the KMD as inputs to rank alternatives. A comparison of the KE-GRA-TOPSIS, KE-TOPSIS, KE-GRA, GRA-TOPSIS, and TOPSIS is conducted to illustrate the unique merits of the KE-GRA-TOPSIS method in Kansei evaluation. Finally, taking the electric drill as an example, we describe the process of the proposed method in detail, which achieves a symmetry between the objectivity of products and subjectivity of users.
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Wooten, Hailey, Hwanhee Kim, Amanda Rakhshandeh, and Anoosh Rakhshandeh. "PSV-8 Glucocorticoid receptor agonist (GRA): what is the best delivery method to newly weaned pigs?" Journal of Animal Science 98, Supplement_3 (2020): 158–59. http://dx.doi.org/10.1093/jas/skaa054.279.
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Abstract We previously found that i.m. injection of GRA, similar to in-feed antibiotics, improves measures of intestinal integrity, nutrient digestibility, and overall growth performance in nursery pigs. In addition, we have demonstrated that the mitigating effects of GRA on the stress of weaning is predominantly done by subsiding the inflammatory response that often accompanies early weaning. The objective of the current study was to explore the most practical methods for delivering GRA to newly weaned pigs. One-hundred and sixty-seven PIC pigs were weaned at 25 ±1.0 days of age (BW 7 ±1.2 kg), and assigned to fourteen treatments (3-4 pigs /pen; 3 pens/treatment). Seven treatments were tested within two sexes (gilts vs. barrows). The treatments were: 1) i.m. injection of GRA (two injections, 0.2 mg/kg BW at -1 and 3 d post-weaning), 2) two levels of in-water GRA (0.8 and 1.6 ppm), 3) in-feed GRA (2.5 and 5.0 ppm), 4) in-feed antibiotic (ANT, 100 ppm tylosin), and 5) control. Dexamethasone was used as GRA. Pigs had free access to in-feed or in-water GRA or ANT during the 1st-week post-weaning. Parameters of growth performance were measured weekly until the end of the nursery phase. A completely randomized design and repeated measurement ANOVA (PROC MIXED) in SAS were used for statistical analyses. In-water, in-feed, and i.m. GRA treatments resulted in growth performance outcomes comparable to that of in-feed ANT. Relative to CON pigs, both ANT and GRA improved ADG and G: F during the nursery phase (P < 0.05). Among the delivery methods tested, 2.5 ppm of in-feed GRA resulted in superior ADG (GRA vs. CON; 0.29 vs. 0.20 kg/d) and G: F (0.63 vs. 0.40 ± 0.05), compared to the control group (P < 0.02). Collectively, these results suggested that in-feed treatment is the best method for delivering GRA to newly weaned pigs.
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Dwi Satria, Muhammad Najib, Erliyan Redy Susanto, Setiawansyah, Sufiatul Maryana, and Pritasari Palupiningsih. "Modification of Grey Relational Analysis for Dynamic Criteria Weighting in Decision-Making Systems." IIUM Engineering Journal 26, no. 2 (2025): 187–203. https://doi.org/10.31436/iiumej.v26i2.3494.
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Grey relational analysis (GRA) is a grey system theory method used to solve multi-criteria decision problems with incomplete or uncertain data. The GRA analyzes the level of closeness or relationship between several alternatives based on a series of criteria. One of the limitations in using the GRA method is the weight of the criteria, which is often fixed or subjective. In many GRA applications, the criterion weights are set based on expert considerations or decision-maker preferences, which can be highly subjective and influenced by individual biases. Grey relational analysis change data driven (GRA-C) method emphasizes the increased effectiveness and flexibility of this method in performance appraisal for multi-criteria decision-making. GRA-C allows for more precise adjustments according to the importance of each criterion, leading to more accurate and relevant evaluation results. By modifying the weights, the GRA-C becomes more flexible and can be adapted to different contexts and specific decision-making needs, so that it can be applied in various industry sectors. These modifications help reduce bias due to improper weight allocation, resulting in more objective performance assessments. The results of the modified GRA-C can provide better insights for decision-makers, supporting a more effective and informed decision-making process. The comparison with the Spearman correlation shows that the GRA-C method has a very strong degree of conformity in producing alternative rankings, with a correlation value 1. This indicates that these methods provide similar results, making them reliable for consistent decision-making. ABSTRAK: Analisis Perhubungan Kelabu (Grey Relational Analysis, GRA) merupakan satu kaedah dalam teori sistem kelabu yang digunakan untuk menyelesaikan masalah keputusan berbilang kriteria (multi-criteria decision-making) yang melibatkan data tidak lengkap atau tidak pasti. GRA menganalisis tahap keterkaitan atau hubungan antara beberapa alternatif berdasarkan satu siri kriteria. Salah satu kekangan dalam penggunaan kaedah GRA ialah pemberat kriteria yang sering kali bersifat tetap atau subjektif. Dalam banyak aplikasi GRA, pemberat kriteria ditentukan berdasarkan pertimbangan pakar atau keutamaan pembuat keputusan, yang boleh menjadi sangat subjektif dan dipengaruhi oleh bias individu. Kaedah Grey Relational Analysis Change Data Driven (GRA-C) menekankan keberkesanan dan fleksibiliti yang lebih tinggi dalam penilaian prestasi bagi sistem keputusan berbilang kriteria. GRA-C membolehkan pelarasan yang lebih tepat mengikut kepentingan setiap kriteria, yang membawa kepada keputusan penilaian yang lebih tepat dan relevan. Dengan pengubahsuaian pemberat, GRA-C menjadi lebih fleksibel dan boleh disesuaikan dengan pelbagai konteks serta keperluan khusus dalam membuat keputusan, membolehkannya diaplikasikan dalam pelbagai sektor industri. Pengubahsuaian ini membantu mengurangkan bias akibat pengagihan pemberat yang tidak sesuai, sekali gus menghasilkan penilaian prestasi yang lebih objektif. Hasil daripada GRA-C yang telah diubah suai dapat memberikan pandangan yang lebih baik kepada pembuat keputusan, seterusnya menyokong proses membuat keputusan yang lebih berkesan dan berasaskan maklumat. Perbandingan dengan korelasi Spearman menunjukkan bahawa kaedah GRA-C mempunyai tahap kesesuaian yang sangat tinggi dalam menghasilkan kedudukan alternatif, dengan nilai korelasi sebanyak 1. Ini menunjukkan bahawa kaedah-kaedah tersebut memberikan hasil yang serupa dan boleh dipercayai untuk proses membuat keputusan yang konsisten.
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Majumder, Priyanka, and Valerio Antonio Pamplona Salomon. "Intuitionistic Fuzzy Ordinal Priority Approach with Grey Relational Analysis." Mathematics 12, no. 19 (2024): 3156. http://dx.doi.org/10.3390/math12193156.
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Multi-attribute decision-making (MADM) is a methodology for solving decision problems with a finite set of alternatives. The several methods of MADM require weights for the criteria and the alternatives to provide a solution. The Ordinal Priority Approach (OPA) is a recently proposed method for MADM that innovates; it does not require these inputs, just the rankings of criteria and alternatives. This article introduces a new hybrid method for MADM: the Intuitionistic Fuzzy Ordinal Priority Approach with Grey Relational Analysis (OPA-IF-GRA). OPA-IF-GRA combines GRA with OPA-IF, a newer extension of OPA that includes intuitionistic fuzzy sets to incorporate uncertainty into the decision-making process. The article presents an OPA-IF-GRA application for solving an electronics engineering problem, considering four criteria and six alternatives. The solution of OPA-IF-GRA is compared with the solutions obtained with three other MADM methods.
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Arshad, Muhammad Waqas, Setiawansyah Setiawansyah, and Sanriomi Sintaro. "Comparative Analysis of the Combination of MOORA and GRA with PIPRECIA Weighting in the Selection of Warehouse Heads." BEES: Bulletin of Electrical and Electronics Engineering 4, no. 3 (2024): 112–22. http://dx.doi.org/10.47065/bees.v4i3.4922.
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The Head of Warehouse has the main responsibility to manage and supervise the daily operations of the warehouse, including receiving, storing, and dispensing goods. In addition, the warehouse head is responsible for leading the warehouse staff team, providing the necessary direction, training, and supervision to ensure efficiency and safety in warehouse operations. This study aims to select warehouse heads by applying a combination of MOORA and PIPRECIA methods, as well as GRA and PIPRECIA. The combination of MOORA and PIPRECIA as well as GRA and PIPRECIA will be compared based on the final ranking of the two methods used. Based on the ranking results on the MOORA Method, the highest value with a value of 0.40017 was obtained by FHY with rank 1, a value of 0.36637 was obtained by AGL with rank 2, and a value of 0.35721 was obtained by YLS with rank 3 Based on the rating results on the GRA Method, the highest value with a value of 0.12164 was obtained by AGL with rank 1, a value of 0.12017 was obtained by FHY with rank 2, and a value of 0.1054 obtained by TAN with rank 3. Ranking differences between Multi-Method Objective Optimization by Ratio Analysis (MOORA) and Gray Relational Analysis (GRA) can arise due to differences in approaches in evaluating and comparing alternatives. The results of the conformity test can be concluded in the selection of warehouse heads who recommend the GRA method compared to the MOORA method, because the results of the conformity level of the GRA method get a value of 99.99919% higher than the MOORA method.
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Setiawansyah, Setiawansyah, Yuri Rahmanto, Ahmad Ari Aldino, Aditia Yudhistira, Pritasari Palupiningsih, and Ari Sulistiyawati. "Hybrid Logarithmic Percentage Change-Driven Objective Weighting and Grey Relational Analysis Method in Employee Contract Renewal." TIN: Terapan Informatika Nusantara 4, no. 12 (2024): 758–68. http://dx.doi.org/10.47065/tin.v4i12.5121.
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Contract employees are individuals who are hired for a specific period of time within a company or organization for a specific purpose. They usually do not have permanent employee status and are bound by work contracts that govern their tenure, salary, and other obligations. Despite not having long-term job security, contract employees often bring specialized skills or experience needed for specific projects. They are often instrumental in handling temporary projects, fulfilling temporary company needs, or filling temporary vacancies. One of the main problems in determining employee contract renewal is the lack of transparency and clear communication from the company. Employees often feel confused or uncertain about the criteria used by management in determining whether or not their contract will be renewed. Lack of clear information can cause anxiety and uncertainty among employees, and impair their performance and motivation. Hybrid Logarithmic Percentage Change-Driven Objective Weighting and Grey Relational Analysis (HLOPCOW-GRA) is an approach that combines two analysis methods, namely LOPCOW and GRA to improve accuracy and reliability in decision making. HLOPCOW-GRA provides an advantage in combining LOPCOW's advantage in handling dynamic data fluctuations with GRA's advantage in analyzing relative relationships between criteria, this approach allows decision makers to gain a deeper understanding of the factors that affect the final outcome. The results of alternative ranking showed that the first place with a GRA final value of 0.1406 was obtained by EM alternatives, second place with a GRA final value of 0.1366 was obtained by SVR alternatives, third place with a GRA final value of 0.1366 was obtained by SVR alternatives, third place with a GRA final value of 0.1406 was obtained by EM alternatives. The final GRA value of 0.1245 obtained alternative ASR.
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Li, Lan Yun, Zhuan Zhao Yang, Xiao Li, and Zhi He. "Research on Fault Recognition for Centrifugal Compressor Using Entropy Weight-Based Gray Relational Analysis." Applied Mechanics and Materials 29-32 (August 2010): 685–90. http://dx.doi.org/10.4028/www.scientific.net/amm.29-32.685.
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A new fault recognition method for centrifugal compressor was proposed by using entropy weight-based gray relational analysis (EW-GRA). Firstly, the weight values of all fault features were calculated objectively by the entropy method to avoid the influence of subjective factors. Secondly, an improved local gray relational coefficient (LGRC) formula with weight measures was designed to reflect the contributions of different fault features. Thirdly, according to the relationship between similarity degree and Euclidean distance, the local gray relational distances (LGRD), the global gray relational distances (GGRD) and the global gray relational grades (GGRG) were calculated, and consequently, the fault recognition result was obtained by using the max membership degree principle. Finally, the engineering practicability and validity of the EW-GRA method was demonstrated by a centrifugal compressor fault diagnosis example, and the results show that the EW-GRA method is more effective and accurate than the traditional gray relational analysis (T-GRA) method and the weighted gray relational analysis (W-GRA) method.
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V.P, Ravi, Raja M, Balusamy T, Anbarasan P, and Sankaran R.A. "Analysis of ECM performance using critic GRA method." International Journal of Basic and Applied Sciences 14, no. 1 (2025): 23–31. https://doi.org/10.14419/rgh5jx90.
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A hybrid CRITIC-GRA method is adopted to determine the best possible parameter combinations for the ECM drilling process. The input process parameters considered were voltage, duty cycle, and electrolyte concentration. The performance measures considered are machining rate (MR), overcut (OC), and surface corrosion factor (SCF). CRITIC evaluates the standard deviations as 0.33, 0.29, and 0.29 for MR, OC, and SCF respectively. The weights were calculated as 0.327, 0.238, and 0.435 for MR, OC, and SCF respectively. It was evaluated that voltage at level 3 (9V), duty cycle at level 3 (90%), and electrolyte concentration at level 2 (30gm/l), were the ideal combination for the ECM drilling process. Duty cycle and electrolyte concentration were shown to be the most important parameters influencing quality features based on the ANOVA results. The confirmation results have improved the GRG by 0.1309 from the initial value.
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Zhao, Hongzhi, and Fengqiang Zhang. "Combined Probabilistic Linguistic Group Decision-Making for Quality Evaluation of Continuing Education for Primary and Secondary School Teachers." International Journal of Decision Support System Technology 17, no. 1 (2025): 1–24. https://doi.org/10.4018/ijdsst.368248.
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With the advancement of material and spiritual aspects of society, alongside improvements in economic, political, technological, and educational systems, continuing education for primary and secondary school teachers has developed rapidly. Evaluating the quality of continuing education programs is a complex task that falls under the category of multiple attribute group decision-making (MAGDM). Recently, methods like Exponential TODIM (ExpTODIM) and grey relational analysis (GRA) have been used to address such challenges, providing effective tools for handling decisions involving multiple criteria. This manuscript proposes a novel method, the probabilistic linguistic ExpTODIM-GRA (PL-ExpTODIM-GRA) approach, to tackle MAGDM problems under PLTSs. By combining the advantages of ExpTODIM and GRA, this method provides a robust framework for evaluating the quality of continuing education for primary and secondary school teachers. To validate the proposed method, a numerical case study is presented, demonstrating its application in real-world evaluations of teacher education programs.
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Wang, Chun, Weihua Zhang, Cong Wu, Heng Hu, and Wenjia Zhu. "Combined Prediction Method of Short-Term Distance Headway Based on EB-GRA-TCN." Journal of Advanced Transportation 2022 (November 7, 2022): 1–12. http://dx.doi.org/10.1155/2022/6456186.
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As an essential parameter to represent vehicle following characteristics, distance headway (DHW) plays an essential role in microtraffic flow simulation, traffic control, and traffic safety alarm. However, due to the randomness, nonlinearity, and correlation of DHW data, constructing DHW prediction models is difficult. Moreover, few studies have considered the time correlation between the historical DHW and the target DHW. To solve the above problems, a DHW prediction model is proposed in this paper by integrating entropy-based grey relation analysis (EB-GRA) and temporal convolutional network (TCN), named as EB-GRA-TCN model. In the model, the EB-GRA is adopted to calculate the correlation between the target DHW and historical DHW sequences, and the DHW data with high correlation are dynamically selected as the optimal input of the DHW prediction model. Then, the TCN algorithm is used to train the DHW prediction model. The TCN architecture integrates the advantages of recurrent neural network (RNN) and convolutional neural network (CNN), which could fully use the previous DHW information. In the experiment, the DHW data from Hefei Expressway are utilized for training the EB-GRA-TCN model. The prediction results showed that the average root mean square error (RMSE) and mean absolute error (MAE) of the proposed model were 0.115 and 0.090, respectively, in the 5, 10, and 15 predicted steps. Compared with the autoregressive integrated moving average (ARIMA), TCN, RNN, and long short-term memory (LSTM) models, the EB-GRA-TCN model achieved the best prediction accuracy. The results indicated that the EB-GRA-TCN model obtained good predictive performance and could provide support for road traffic control and traffic safety warming.
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Wang, Xiaolei, and Yingzhao He. "Multiple Channel Integration Quality Assessment Method Using NARX." Complexity 2020 (November 20, 2020): 1–9. http://dx.doi.org/10.1155/2020/6650343.
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To improve the accuracy of the multiple channel integration quality (MCIQ) evaluation, this paper proposes a comprehensive evaluation method using the nonlinear autoregressive exogenous model (NARX) and constructs an index system. First, the entropy method is used to determine the objective weight of each indicator. The indicators used in this paper are process consistency, information consistency, emotional value, procedural value, service structure transparency, online result value, business relevance, and online purchase intention. Second, an improved gray relational analysis (GRA) algorithm is used to obtain the comprehensive gray relational degree between the above eight indicators’ standard samples and the tested samples. Then, this study uses the dataset preprocessed with the GRA algorithm for training the NARX model. Then, this study uses the trained model to evaluate the quality of multiple channel integration comprehensively. Next, this study uses standardized methods to quantify the evaluation results to provide new ideas and theoretical guidance for teaching traditional retailers to use the advantages of multiple channels to expand their online business. This paper uses 50,000 consecutive samples of a product for 3 months as a dataset in the experimental part. Through the GRA method and the NARX model, the comprehensive gray relational degree between the test sample and the ideal sample is obtained, and the results are quantified. Experiments show that, compared with the GRA method, this paper’s method has a higher degree of fit between the output value and the target value.
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Wooten, Hailey, Hwanhee Kim, Amanda R. Rakhshandeh, and Anoosh Rakhshandeh. "Glucocorticoid Receptor Agonists to Improve the Productivity and Health of Early-Weaned Pigs: What Is the Best Method of Delivery?" Animals 10, no. 7 (2020): 1124. http://dx.doi.org/10.3390/ani10071124.
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The purpose of the current study was to determine the best method of delivery for glucocorticoid receptor agonist (GRA) treatment. A total of 167 Pig Improvement Company (PIC) piglets (body weight (BW) 7.35 ± 1.24 kg) were weaned at 25.0 ± 0.81 days of age and randomly assigned to 14 treatment groups based on a 2 × 7 factorial arrangement with sex (gilts vs. barrows), in-feed antibiotic (ANT; 110 mg/kg in-feed tylosin), repeated intramuscular (I.M.) injection of GRA (two injections, 0.2 mg/kg BW dexamethasone (DEX)), low dose in-feed GRA (LF, 2.5 mg/kg diet DEX ), high dose in-feed GRA (HF, 5 mg/kg diet DEX), low dose in-water GRA (LW, 0.8 mg/L DEX ), high dose in-water GRA (HW, 1.6 mg/L DEX ), and no treatment control (CON) as the main factors. Body weight and feed intake were measured daily from days 0 to 7 and weekly from days 7 to 28 post-weaning. The interaction effect for average daily gain (ADG) was significant with gilts performing better in the I.M., ANT, and LF groups (p = 0.05). All treatment groups, with the exception of the HW group, had a higher ADG than the CON group. Gilts in the I.M., LF, and HF groups had the highest ADG compared to other treatment groups (p ≤ 0.05). Sex and the interaction between sex and treatments had no effect on the gain-to-feed ratio (G:F; p ≥ 0.21). All treatment groups had a higher G:F than the CON group (p ≥ 0.04). These results suggest that the low-dose, in-feed GRA treatment is the best GRA delivery method and is a suitable alternative to in-feed sub-therapeutic antibiotics.
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Ahmad, Niyaz, Rizwan Ahmad, Md Aftab Alam, Farhan Jalees Ahmad, and Rehan Abdur Rub. "Quantification and Evaluation of Glycyrrhizic Acid-loaded Surface Decorated Nanoparticles by UHPLC-MS/MS and used in the Treatment of Cerebral Ischemia." Current Pharmaceutical Analysis 16, no. 1 (2019): 24–39. http://dx.doi.org/10.2174/1573412914666180530073613.
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Background: Glycyrrhizic Acid (GRA), a potent antioxidant triterpene saponin glycoside and neuroprotective properties exhibits an important role in the treatment of neurological disorders i.e. cerebral ischemia. GRA is water soluble, therefore it’s have low bioavailability in the brain. Objective: To enhance brain bioavailability for intranasally administered Glycyrrhizic Acidencapsulated- chitosan-coated-PCL-Nanoparticles (CS-GRA-PCL-NPs). Methods: Chitosan-coated-PCL-Nanoparticles (CS-PCL-NPs) were developed through double emulsification- solvent evaporation technique and further characterized for particle size, zeta potential, size distribution, encapsulation efficiency as well as in vitro drug release. UPLC triple quadrupole Qtrap MS/MS method was developed to evaluate brain-drug uptake for optimized CS-GRA-PCL-NPs and to determine its pharmacokinetic in rat’s brain as well as plasma. Results: Mean particles size (231.47±7.82), polydispersity index (PDI) i.e. (0.216±0.030) and entrapment efficiency (65.69±5.68) was determined for developed NPs. UPLC triple quadrupole Qtrap MS/MS method study showed a significantly high mucoadhesive potential of CS-GRA-PCL-NPs and least for conventional and homogenized nanoformulation; elution time for GRA and internal standard (IS) Hydrocortisone as 0.37 and 1.94 min at m/z 821.49/113.41 and 363.45/121.40 were observed, respectively. Furthermore, intra and inter-assay (%CV) of 0.49-5.48, %accuracy (90.00-99.09%) as well as a linear dynamic range (10.00 ng/mL -2000.0 ng/mL), was observed. Pharmacokinetic studies in Wistar rat brain exhibited a high AUC0-24 alongwith an amplified Cmax (p** < 0.01) as compared to i.v. treated group. Conclusion: Intranasal administration of developed CS-coated-GRA-loaded-PCL-NPs enhanced the drug bioavailability in rat brain along with successfully UPLC-MS/MS method and thus preparation of GRA-NPs may help treat cerebral ischemia effectively. The toxicity studies performed at the end revealed safe nature of optimized nanoformulation.
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Li, Ma, and Pengyuan Dong. "Identification of voltage sag source based on Improved GRA." Journal of Physics: Conference Series 2258, no. 1 (2022): 012075. http://dx.doi.org/10.1088/1742-6596/2258/1/012075.
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Abstract Accurate identification of fault source causing voltage sag is of great significance to the governance and further research of voltage sag. In this paper, a voltage sag source identification method based on improved grey correlation analysis (GRA) is proposed. In view of the deficiency that the traditional GRA only considers the similarity, the proposed method considers the geometric area and slope of sequence into the calculation of correlation coefficient, so that the improved GRA has attributes of both sequence similarity and data closeness. Eight features are extracted from six common types of sag waveforms to form standard and test sequence; The improved GRA is used to calculate the correlation degree between the test and standard sequences, then the identification of sag source can be realized. Simulation model is built in MATLAB. Results show that this proposed method can effectively identify the voltage sag source. Compared with the traditional GRA, this method has higher identification accuracy and stronger identification ability.
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Maidin, Nurul Ain, Mohd Sapuan Salit, Mastura Mohammad Taha, and Mohd Zuhri Mohamed Yusoff. "Conceptual Design and Selection of Natural Fibre Reinforced Composite Cyclist Helmet Liner Using an Integrated Approach." Pertanika Journal of Science and Technology 32, no. 1 (2024): 437–51. http://dx.doi.org/10.47836/pjst.32.1.23.
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This paper describes the conceptual design phase in the product development of a natural fibre composites cyclist helmet liner, beginning with idea generation and ending with selecting the best design concept. The integrated Theory of Inventive Problem Solving (TRIZ), Biomimetic methods, and the Grey Relational Analysis (GRA) method are demonstrated in this paper. This work aims to produce nature-inspired design concepts and determine the best design concept for the composite cyclist helmet liner. Following that, four design concepts were generated using the TRIZ-Biomimetic method, and the variance of concepts was developed using a morphological chart. The GRA method was chosen as the multiple criteria decision-making tool to compare their cost and weight criteria. The design concept C1 was selected as the best design concept for the natural fibre composites of cyclist helmet liner conceptual design when the highest grey relational grade (GRG) value and rank with a value of 1.0000 satisfied the GRA method conditions. This paper demonstrates how the integrated method of TRIZ-Biomimetics-Morphological Chart and GRA helps researchers and engineers develop designs inspired by nature and select the best design concept during the conceptual design stage using a systematic strategy and justified solutions.
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Chen, Yi, Hanqiang Li, Haifeng Dou, Hong Wen, and Yu Dong. "Prediction and Visual Analysis of Food Safety Risk Based on TabNet-GRA." Foods 12, no. 16 (2023): 3113. http://dx.doi.org/10.3390/foods12163113.
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Food safety risk prediction is crucial for timely hazard detection and effective control. This study proposes a novel risk prediction method for food safety called TabNet-GRA, which combines a specialized deep learning architecture for tabular data (TabNet) with a grey relational analysis (GRA) to predict food safety risk. Initially, this study employed a GRA to derive comprehensive risk values from fused detection data. Subsequently, a food safety risk prediction model was constructed based on TabNet, and training was performed using the detection data as inputs and the comprehensive risk values calculated via the GRA as the expected outputs. Comparative experiments with six typical models demonstrated the superior fitting ability of the TabNet-based prediction model. Moreover, a food safety risk prediction and visualization system (FSRvis system) was designed and implemented based on TabNet-GRA to facilitate risk prediction and visual analysis. A case study in which our method was applied to a dataset of cooked meat products from a Chinese province further validated the effectiveness of the TabNet-GRA method and the FSRvis system. The method can be applied to targeted risk assessment, hazard identification, and early warning systems to strengthen decision making and safeguard public health by proactively addressing food safety risks.
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Huang, Xiong, Changsheng Shi, and Yuepeng Yan. "Prediction of Gas Emission in Mining Face Based on GRA-ISA-LSSVM." International Journal of Natural Resources and Environmental Studies 5, no. 2 (2025): 136–50. https://doi.org/10.62051/ijnres.v5n2.18.
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Coal, as a crucial primary energy source in China, provides a stable energy supply and security for the nation's economic and sustainable high-quality development. However, gas disasters can lead to severe casualties and significant economic losses. Therefore, accurately and efficiently predicting gas emission is of paramount importance and holds significant practical value for the safe production of high-gas mines. This paper employs the Least Squares Support Vector Machine (LSSVM) model, which offers better regression prediction accuracy for nonlinear problems with small datasets. To enhance the model's prediction accuracy and effectiveness, the Grey Relational Analysis (GRA) method is used to analyze the influencing factors of gas emission. Factors with high correlation are selected as model inputs. Experimental results show that coal seam gas content, coal seam depth, coal seam thickness, adjacent seam gas content, adjacent seam spacing, mining face length, and adjacent seam thickness have high correlation. To validate the results, Kendall's tau-b, Pearson, and Spearman correlation analysis methods are used, and the experimental results align with GRA. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Improved Simulated Annealing Algorithm (ISA) are employed to find the global optimal solution for the LSSVM model parameters. Finally, the GRA-GA-LSSVM, GRA-PSO-LSSVM, and GRA-ISA-LSSVM models are constructed and tested. Experimental results show that after applying GRA, the RMSE and MAE metrics decrease, while the R² metric increases, proving that the GRA method optimizes the model. The GRA-ISA-LSSVM model has the lowest RMSE and MAE values and the highest R² value, indicating superior performance in static gas emission prediction.
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V. Chengal, Reddy, S. Kavitha, T. Nishkala, and Basha S. M. Jameel. "Multi objective optimization of 3D printing process using multi-attribute decision making methods." i-manager's Journal on Mechanical Engineering 12, no. 2 (2022): 40. http://dx.doi.org/10.26634/jme.12.2.18562.
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Fused deposition modeling (FDM) is one of the additive manufacturing (AM) methods widely used in many divisions, especially medical implants and aerospace, due to capabilities to build complex 3D objects and geometries. However, quality and dimensional accuracy of the FDM parts are significantly influenced by the various FDM process parameters including filament wire material. In the present work, new filament wire material Thermoplastic Polyurethane (TPU) was utilized to produce FDM parts. Hence, deciding the optimum process parameters is very critical to produce the FDM parts with good surface quality (Ra) and dimensional accuracy (Δd) concurrently using TPU material. In this paper, the author has contributed to determine the optimum 3D printing process parameters to improve the quality and accuracy for the new filament wire material Thermoplastic Polyurethane (TPU) using multi-attribute decision making (MADM) methods namely Gray Relational Analysis (GRA) and technique for order preference by similarity to ideal solution (TOPSIS). Further, the results of GRA and TOPSIS techniques were compared and concluded that TOPSIS method substantially reduced the surface roughness to a value of 12% contrast to the GRA method whereas the dimensional deviation accuracy increased to 6.25% over the GRA method.
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Feng, B., W. Xu, R. S. Wu, X. B. Xie, and H. Wang. "Finite-frequency traveltime tomography using the Generalized Rytov approximation." Geophysical Journal International 221, no. 2 (2020): 1412–26. http://dx.doi.org/10.1093/gji/ggaa067.
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SUMMARY Wave-equation-based traveltime tomography has been extensively applied in both global tomography and seismic exploration. Typically, the traveltime Fréchet derivative is obtained using the first-order Born approximation, which is only satisfied for weak velocity perturbations and small phase shifts (i.e. the weak-scattering assumption). Although the small phase-shift restriction can be handled with the Rytov approximation, the weak velocity-perturbation assumption is still a major limitation. The recently developed generalized Rytov approximation (GRA) method can achieve an improved phase accuracy of the forward-scattered wavefield, in the presence of large-scale and strong velocity perturbations. In this paper, we combine GRA with the classical finite-frequency theory and propose a GRA-based traveltime sensitivity kernel (GRA-TSK), which overcomes the weak-scattering limitation of the conventional finite-frequency methods. Numerical examples demonstrate that the accumulated time delay of forward-scattered waves caused by large-scale smooth perturbations can be correctly handled by the GRA-TSK, regardless of the magnitude of the velocity perturbations. Then, we apply the new sensitivity kernel to solve the traveltime inverse problem, and we propose a matrix-free Gauss–Newton method that has a faster convergence rate compared with the gradient-based method. Numerical tests show that, compared with the conventional adjoint traveltime tomography, the proposed GRA-based traveltime tomography can obtain a more accurate model with a faster convergence rate, making it more suited for recovering the large-intermediate scale of the velocity model, even for strong-perturbation and complex subsurface structures.
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Cai, Ziwen, Yutao Xu, Yong Xiao, Dunhui Chen, Yun Zhao, and Zhukui Tan. "Regional electrical energy substitution potential prediction based on time series and improved back propagation neural network." Journal of Physics: Conference Series 2636, no. 1 (2023): 012029. http://dx.doi.org/10.1088/1742-6596/2636/1/012029.
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Abstract A combined time-series-based regression forecasting and GRA-IPSO-BP structure is proposed to forecast the electricity replacement forecasts using a time series model based on the triple exponential smoothing forecasting method. The forecast results are corrected using the GRA-IPSO-BP structure. The results of the algorithm show that using a combination of time series and GRA-IPSO-BP structure can significantly improve the forecasting accuracy of electricity replacement compared to single-method forecasting.
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Capaldi, Elizabeth D., John V. Lombardi, and Victor Yellen. "Improving Gra Duation Rates: A Simple Method That Works." Change: The Magazine of Higher Learning 38, no. 4 (2006): 44–50. http://dx.doi.org/10.3200/chng.38.4.44-50.
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Liu, Aijun, Xingru Guo, Taoning Liu, et al. "A GRA-Based Method for Evaluating Medical Service Quality." IEEE Access 7 (2019): 34252–64. http://dx.doi.org/10.1109/access.2019.2903684.
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Shi, Huan, and Lu Gan. "Evaluation for Village Development Based on GRA-TOPSIS Method." IOP Conference Series: Earth and Environmental Science 455 (March 25, 2020): 012194. http://dx.doi.org/10.1088/1755-1315/455/1/012194.
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Xue-jun, Tang, and Chen Jia. "A Dynamic Interval Decision-Making Method Based on GRA." Physics Procedia 24 (2012): 2017–25. http://dx.doi.org/10.1016/j.phpro.2012.02.296.
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Kolhapure, Rakesh, Manjunath Rawal, Suyog Rayjadhav, et al. "Shape optimization of washer load cell using GRA method." Materials Today: Proceedings 27 (2020): 238–43. http://dx.doi.org/10.1016/j.matpr.2019.10.106.
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Weng, Xiangjian, and Shan Yang. "Private-Sector Partner Selection for Public-Private Partnership Projects Based on Improved CRITIC-EMW Weight and GRA -VIKOR Method." Discrete Dynamics in Nature and Society 2022 (September 13, 2022): 1–10. http://dx.doi.org/10.1155/2022/9374449.
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When the government decides to use the public-private partnership (PPP) in projects, such as infrastructure construction, selecting a private-sector partner that meets the project's needs is one of the key factors for successful implementation, but this is ignored in existing research. On this basis, this paper proposes a GRA-VIKOR method based on the combined weight of the improved CRITIC-entropy weight method (EWM). The traditional CRITIC method is improved by combining it with EWM. The combined weights are measured, which reduces the limitations of the single weight. Considering the inherent correlation of evaluation indicators, the VIKOR method is combined with the grey relational analysis (GRA), which makes the results of the selection assessment more reasonable. This paper carries out a case study of the first inland navigation PPP project in China. Through preliminary tracking studies, it tests the effectiveness of the proposed method, the superiority of which is demonstrated by comparing the evaluation results with those of the traditional GRA methods, VIKOR, and TOPSIS.
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Wang, Li Jiu, and Li Li. "Development of a Method in Evaluation and Adjustment for Consistency of Group Decision-Making Based on Grey Relational Analysis and its Application in Evaluation of New Rural Economic Building Materials." Advanced Materials Research 168-170 (December 2010): 1163–68. http://dx.doi.org/10.4028/www.scientific.net/amr.168-170.1163.
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In this paper, grey relational analysis (GRA) was used in consistency test of group judgment matrixes. The evaluation indicator weight was obtained through the judgment matrix calculated with expert evaluating method in analytical hierarchy process (AHP). The judgment method and the adjustment process for consistency of group judgment matrixes were studied. First, the consistency indicators were put forward, and then the definitions and the theorems of consistency indicators in the judgment method were defined based on GRA. Then the theorems were given proof. A method using GRA to judge the consistency of group judgment matrixes was proposed for the first time. Second, adjustment modeling was developed to solve the consistency of group judgment matrixes. Finally, the applications of the judgment method and the adjustment process have been illustrated by given example. It is believed that the proposed methods are applicable to test consistency of evaluation indicators of new rural economic building materials.
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Qi, Yong, Chen Zhu, Fang Wang, and Yu Xia. "Grey relational analysis method for typhoon vulnerability assessment of civil engineering structures based on the 2-tuple linguistic neutrosophic number." PLOS ONE 17, no. 11 (2022): e0277539. http://dx.doi.org/10.1371/journal.pone.0277539.
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As one of the severe natural disasters, typhoon hazard brings tremendous tragedy to human beings. The foreland in the southeast of China is one of the most typhoon prone areas in the world. There are amount of damage of civil engineering structures induced by typhoon every year. Especially for the spacious villages, the low-rise buildings are vulnerable to typhoon so that many of them are destroyed regionally. The typhoon vulnerability assessment of civil engineering structures is a classical multiple attribute group decision making (MAGDM) issues. In this paper, the 2-tuple linguistic neutrosophic number grey relational analysis (2TLNN-GRA) method is built based on the grey relational analysis (GRA) and 2-tuple linguistic neutrosophic sets (2TLNSs) with incomplete weight information. For deriving the weight information of the attribute, an optimization model is built on the basis of the GRA, by which the attribute weights can be decided. Then, the optimal alternative is chosen through calculating largest relative relational degree from the 2-tuple linguistic neutrosophic number positive ideal solution (2TLNNPIS) which considers both the largest grey relational coefficient (GRC) from the 2TLNNPIS and the smallest GRC form 2-tuple linguistic neutrosophic number negative ideal solution (2TLNN NIS). Then, combine the traditional fuzzy GRA model with 2TLNNSs information, the 2TLNN-GRA method is established and the computing steps for MAGDM are built. Finally, a numerical example for typhoon vulnerability assessment of civil engineering structures has been given and some comparisons is used to illustrate advantages of 2TLNN-GRA method.
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Wang, Qi Bing, and An Hua Peng. "Developing MCDM Approach Based on GRA and TOPSIS." Applied Mechanics and Materials 34-35 (October 2010): 1931–35. http://dx.doi.org/10.4028/www.scientific.net/amm.34-35.1931.
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Multiple criteria decision making(MCDM) is widely used in selection from a set of available alternatives with multiple criteria, approaches to which includes fuzzy comprehensive evaluation(FCE), grey relational analysis(GRA), and technique for order preference by similarity to ideal solution(TOPSIS), and so on. First analyzes the limitations of various methods: only considering the overall effect of attribute indicators in the method of FCE, only considering the shape similarity of data curve between comparative scheme and ideal solution in GRA and only considering position approximation in TOPSIS. Second proposes a new method of comprehensive evaluation which takes into account both shape similarity and position approximation. The validity of this method has been further proved by an example of suppliers selection.
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Naus, Krzysztof, and Piotr Szymak. "Using Interchangeably the Extended Kalman Filter and Geodetic Robust Adjustment Methods to Increase the Accuracy of Surface Vehicle Positioning in the Coastal Zone." Applied Sciences 13, no. 4 (2023): 2110. http://dx.doi.org/10.3390/app13042110.
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This paper presents a study to evaluate the comparative positioning accuracy of Surface Vehicle (SV) using Dead Reckoning (DR), Geodetic Least-Squares Adjustment (GLSA), Geodetic Robust Adjustment (GRA), and External Kalman Filter (EKF) methods. This involved simulating the results of navigational measurements subject to errors (including gross errors) used to position the SV swimming along a given trajectory in the vicinity of three beacons. We showed an apparent increase in the SV positioning accuracy, from approximately 9 m of Root Mean Square (RMS) obtained by DR and GLSA methods, to approximately 2 m (RMS), achieved using GRA and EKF methods. We also showed that, by interchanging GRA and EKF methods, it is still possible to increase the positioning accuracy of the SV up to 1.14 m (RMS). However, such an interchange should occur after the experimentally determined limit of the mean error of the position coordinates estimated by the GRA method has been exceeded.
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Phimoolchat, Jurapun, and Apiwat Muttamara. "Multi-Objective Optimization of Electrical Discharge Machining Parameters for 2024 Aluminum Alloy Using Grey-Taguchi Method." Materials Science Forum 998 (June 2020): 55–60. http://dx.doi.org/10.4028/www.scientific.net/msf.998.55.
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This paper focused on Grey relational analysis (GRA) to optimize EDM parameters through multi-objective optimization for Al2024 aluminum and electrode graphite ISO-63 was used as a cutting tool. The process parameters pulse on time, duty factor, pulse current and open voltage. Performance characteristics examined included material removal rate (MRR), electrode wear ratio (EWR) and surface roughness (SR). Taguchi’s 27 experimental designs, often called an orthogonal array (OA), was utilized to ignore interaction and concentrate on main effect estimation. GRA was performed to optimize input parameters levels. Results were that MRR increased from 35.00 to 35.11 mm3/min, EWR decreased from 11.63 to 10.89 mm3/min, and SR decreased from 5.01 to 4.97 μm. Taguchi and GRA resulted in clear improvements in MRR, EWR, and SR.
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Bouzid, Lakhdar, Amel Chabbi, and Mohemed Athmene Yallese. "Comparative study when modeling and multi-objectif optimization of machining parameters during turning Polyoxymethylene polymer using DFA, GRA and TOPSIS technics." STUDIES IN ENGINEERING AND EXACT SCIENCES 5, no. 3 (2024): e12893. https://doi.org/10.54021/seesv5n3-105.
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This paper examines the effect of the material and machining parameters on cutting force, and surface roughness when turning polyoxymethylene POM C using a carbide tool. Turning experiments were conducted based on the Taguchi orthogonal matrix L16, taking into account cutting speed, cutting feed and cutting depth as input process parameters. Multi-objectif optimization was achieved through DFA, GRA, and TOPSIS methods. Results proved that both GRA and TOPSIS techniques provided a similar optimal parametric condition, namely a Vc = 500 m/min, a f = 0.08 mm/rev and a ap = 1 mm. On the other hand, the DFA method gives the following optimal parameters: Vc = 345.04 m/min, f = 0.09 mm/rev and ap = 1 mm. Experimental approach illustrates the feasibility and effectiveness of these proposed methods GRA and TOPSIS for multi-objectif optimization by contributing to the DFA method.
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Mahmoudi, Amin, Saad Ahmed Javed, Sifeng Liu, and Xiaopeng Deng. "DISTINGUISHING COEFFICIENT DRIVEN SENSITIVITY ANALYSIS OF GRA MODEL FOR INTELLIGENT DECISIONS: APPLICATION IN PROJECT MANAGEMENT." Technological and Economic Development of Economy 26, no. 3 (2020): 621–41. http://dx.doi.org/10.3846/tede.2020.11890.
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The Distinguishing Coefficient (ξ) is an important parameter of Grey Relational Analysis (GRA), a flagship multi-criteria decision making (MCDM) model of Grey System Theory, an intelligent and multifaceted field developed by Chinese scientists in 1980s. However, the scholars widely assume ξ = 0.5. The current study questions this practice. Also, some scholars have argued that the variation in ξ doesn’t influence the ranking of the factors through GRA. On contrary, the study demonstrates, the variation in ξ can influence the ranking. This has been shown through a case involving primary data concerning the perceived relative importance of Project Management Knowledge Areas (PMKAs). This study is significant for the analysts of uncertain systems, represented by grey or fuzzy systems, who intend to use GRA for intelligent multi-criteria decision making. It encourages ξ – driven sensitivity analysis of GRA model before interpreting the results. The study reveals, by tailoring the value of ξ a point can be achieved where the ranking obtained through GRA can be made most comparable to the other MCDM methods. For comparative analysis of the GRA based results the study deployed three other MCDM techniques; Analytic Hierarchy Process, Best Worst Method and Simple Additive Weighting.
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Ozcan, Tuncay, and Fatih Tuysuz. "Modified Grey Relational Analysis Integrated with Grey Dematel Approach for the Performance Evaluation of Retail Stores." International Journal of Information Technology & Decision Making 15, no. 02 (2016): 353–86. http://dx.doi.org/10.1142/s0219622016500073.
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Performance evaluation is one of the most important problems for retail chains and may have effect on tactical and strategic decisions. This paper proposes a grey-based multi-criteria performance evaluation model for retail sector. This model integrates Decision-Making Trial and Evaluation Laboratory (DEMATEL) and modified Grey Relational Analysis (GRA) methods. First, the grey-based DEMATEL method is used for determining the importance of performance indicators to be used in GRA based on the experts’ assessments. Then, the proposed modified GRA method is used for the performance evaluation and ranking of retail stores with respect to the predetermined performance indicators. Finally, the effectiveness and the applicability of the developed approach are illustrated with a case study with the actual data taken from a retail chain in Turkey.
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SIWIEC, Dominika, and Stanislav VANDŽURA. "METHOD OF PREDICTING FAVOURABLE INDUSTRIAL PRODUCTS." Modern Management Review 26, no. 3 (2021): 87–96. http://dx.doi.org/10.7862/rz.2021.mmr.20.
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Predicting favourable products is still challenging. It is influenced by dynamic customers' requirement changes and reduction of waste. An important problem is a simultaneous combination of customer satisfaction with environmental aspects. It resulted from a need to reduce the harmfulness of products and increasing the quality level of these products. Therefore, the aim is to propose a method to predict favourable products considering qualitative and environmental aspects. The method relies on predicting which product will be the most favourable for customer, and simultaneously will be the most environmentally friendly. Due to the uncertainty of decisions, the Grey Relational Analysis (GRA) was implemented in the proposed method. The GRA method is effective to any number of data, therefore the proposed method does not have limitations in numbers of qualitative and environmental criteria. The test was carried out based on harmful industrial products. It was fluorescent penetrants used in popular non-destructive testing.
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Ramachandran, M., Manjula Selvam, and Vidhya Prasanth. "Performance evaluation of Wireless Network selection using Gray Rational Analysis (GRA) Method." 1 1, no. 1 (2022): 9–16. http://dx.doi.org/10.46632/jeae/1/1/2.
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This paper proposes a network selection solution that is user location- and knowledge-based, aiming to diversify by choosing the best value network in a wireless network environment, improving video delivery. When multi-attribute decision making (MADM) techniques are used for wireless network vertical approval, the impact of weighting techniques combined with Gray Rational Analysis (GRA) is studied. Performance analysis of the GRA algorithm is conducted for hierarchical, background, conversational, interactive, and streaming classes of services using Random Weighting (RW) and Least Square Weight (LSW) techniques. In the MCDM context, multiple alternatives (e.g., wireless networks) refer to attributes such as Network 1, Network 2, Network 3, Network 4, and Network 5. Delay (msec), Jitter (msec), BER (x 10), Throughput (kbps), and Cost (units) are used as evaluation methods. In this type of analysis, gray relational analysis (GRA) methods determine the best solution for negative short distances and very long distances to settlement, but do not consider the relative importance of these distances. As a result, Wireless Network 5 ranked first, and Wireless Network 4 ranked the lowest.
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Zhang, Nan, and Yaoyao Shi. "Improvement of cutting force and material removal rate for disc milling TC17 blisk tunnels using GRA–RBF–PSO method." Proceedings of the Institution of Mechanical Engineers, Part C: Journal of Mechanical Engineering Science 233, no. 16 (2019): 5556–67. http://dx.doi.org/10.1177/0954406219848473.
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Blisk is a key component of new aero-engines. To improve machining efficiency, disc milling is used for roughing blisk tunnels. The multi-objective optimization is employed to optimize disc milling process. In this study, an integration-based approach that used grey relational analysis (GRA) coupled with radial basis function (RBF) neural network and particle swarm optimization (PSO) algorithm is applied to solve the optimization problem. To achieve smaller cutting force and greater material removal rate (MRR), the appropriate cutting speed, feed rate per tooth, and cutting height needed to be determined. A hybrid experiment scheme of three factors–five levels is carried out to generate data sample. Results of verified experiments indicate that GRA–RBF–PSO approach can improve performance better than original GRA.
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Zhang, Zhen, and Pengfei Su. "Research on the English Classroom Teaching Effect Evaluation with Interval-Valued Intuitionistic Fuzzy Grey Relational Analysis Method." Mathematical Problems in Engineering 2022 (April 15, 2022): 1–11. http://dx.doi.org/10.1155/2022/7445250.
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The English classroom teaching effect evaluation is looked as the multiattribute group decision-making (MAGDM). Thus, a useful MAGDM algorithm is needed to cope with it. Depending on the classical GRA process and interval-valued IFSs (IVIFSs), this study builds the IVIF-GRA process to assess the English classroom teaching effect. First of all, the concepts of IVIFSs are reviewed. In addition, the weights of criteria are derived through the CRITIC method. Afterwards, the GRA model is extended to IVIFSs to get the final result of the alternative. Therefore, all alternatives could be ranked and the optimal one with English classroom teaching effect can be identified. At last, a given numerical example and some given comparative studies are obtained. The analysis results show that the defined algorithms are effective for solving the English classroom teaching effect evaluation.
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Leman, Dedi. "Sistem Pendukung Keputusan Penentuan Instruktur Terbaik Dengan Kombinasi Metode GADA dan GRA Pada Tecnho Garage." Jurnal Ilmu Komputer dan Sistem Informasi 4, no. 2 (2025): 144–54. https://doi.org/10.70340/jirsi.v4i2.193.
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Instructors play a vital role in the success of training programs at non-formal education institutions such as Techno Garage. The selection of the best instructor has traditionally been conducted manually, making it prone to subjectivity and inconsistency in decision-making. To address this issue, this study designs a web-based decision support system that combines two multi-criteria decision-making methods: Grey Absolute Decision Analysis (GADA) and Grey Relational Analysis (GRA). The GADA method is used to assign relative weights to each criterion and prioritize alternatives based on absolute values, while the GRA method is applied to handle uncertainty and complex relationships among criteria. The evaluation criteria include attendance, length of service, participant feedback, and contributions to material development. The results demonstrate that the combination of GADA and GRA methods provides more objective and accurate recommendations in selecting the best instructor. This system enhances the efficiency, transparency, and accountability of the instructor selection process.
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Shao, Xiao Yan, Xiang Li, and Ling Ling Li. "The Methods of Soil Heavy Metal Pollution Evaluation Using GRA." Advanced Materials Research 282-283 (July 2011): 637–40. http://dx.doi.org/10.4028/www.scientific.net/amr.282-283.637.
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To assess the soil heavy metal pollution, there are so many methods, such as the mono pollution-factor, the comprehensive Nemerow pollution-factor and so on. Grey Relational Analysis (GRA) is one of the major contents of gray system theory. The method of GRA was used in the application of environmental impact assessment, such as water pollution research. In this paper, we designed the new practical method of the heavy metal pollution evaluation, which is focus on six soil heavy metals (Cd, Hg, Pb, Cr, Cu, Zn). According to the consenting range of environment level by the National Environmental Standard (GB15618-1995), we have done our researches.
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Chen. "A New Multi-Criteria Assessment Model Combining GRA Techniques with Intuitionistic Fuzzy Entropy-Based TOPSIS Method for Sustainable Building Materials Supplier Selection." Sustainability 11, no. 8 (2019): 2265. http://dx.doi.org/10.3390/su11082265.
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A new multi-criteria assessment model is proposed in this paper, which combines grey relational analysis (GRA) techniques with intuitionistic fuzzy entropy-based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) method, to solve multi-criteria decision making (MCDM) problems and to sort the alternatives. Generally speaking, the supplier selection process, by which buyers choose to find the right supplier of the high-quality products or/and services within the scheduled and quantity, is one of the most important key activities in constructing an effective and timely supply chain. On account of several conflicting attributes on which the knowledge of decision makers is often inaccurate and vague, this is a difficult problem. The contribution of this paper is not only to substitute objective weights of intuitionistic fuzzy entropy for subjective weights directly made by decision-makers in the TOPSIS method, but also to extend and modify this method with intuitionistic fuzzy sets and GRA techniques, and to propose the intuitionistic fuzzy entropy-based TOPSIS method combined with GRA techniques for selecting appropriate sustainable building materials supplier. Finally, we take the choice of sustainable building materials supplier as an example to illustrate the alternative effectively chosen by the intuitionistic fuzzy entropy-based TOPSIS method combined with GRA techniques.
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Mahmoudi, Amin, Mehdi Abbasi, Xiaopeng Deng, Muhammad Ikram, and Salman Yeganeh. "A novel model for risk management of outsourced construction projects using decision-making methods: a case study." Grey Systems: Theory and Application 10, no. 2 (2020): 97–123. http://dx.doi.org/10.1108/gs-09-2019-0038.
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PurposeSelecting a suitable contract to outsource construction projects is an ongoing concern for project managers and organizational directors. This study aims to propose a comprehensive model to manage the risks of outsourced construction project contracts.Design/methodology/approachTo employ the proposed model, firstly, the types of contracts and risks in the organization should be identified, then, to prioritize the contracts, the identified risks are considered as criteria. After receiving the experts' opinions, the best–worst method (BWM) integrated with grey relation analysis (GRA) method was used to prioritize the contracts. BWM and GRA are multi-criteria decision-making methods with different approaches and applications. In the current study, BWM has been employed to calculate the weights of criteria because it has better performance than other methods such as the analytic hierarchy process (AHP). After calculating the weights of criteria, the GRA method has been utilized for ranking the alternatives.FindingsAccording to the results obtained from the case study, the cost plus award fee contract is the most suitable alternative for outsourcing construction projects. The proposed methodology can be practically applied through different types of the projects such as construction or “engineering, procurement and construction”.Originality/valueTo the best of our knowledge, this is the first time a conceptual model has been proposed to select an appropriate contract for construction projects. Also, for the first time, the BWM integrated with GRA method has been used to prioritize project contracts based on the potential risks. The proposed model can contribute to project managers for selecting a suitable contract with the least risk in construction projects.
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Pires, Luiz F., and Fábio A. M. Cássaro. "Nuclear Laboratory Setup for Measuring the Soil Water Content in Engineering Physics Teaching Laboratories." AgriEngineering 5, no. 2 (2023): 1079–89. http://dx.doi.org/10.3390/agriengineering5020068.
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Soil water content (θ) is a crucial soil parameter that is determined in many studies involving engineering, geology, and soil and environmental sciences. For instance, evaluating the soil strength, groundwater recharge, hydraulic conductivity, and soil aeration status depends on θ. The measurement of θ is fundamental for monitoring and controlling several soil processes. The gamma-ray attenuation (GRA) technique is a fast and non-destructive way of evaluating θ in soils with very contrasting compositions. Although, GRA is rarely explored in lab physics classes. The proposal of an experiment using a teaching GRA apparatus for measuring θ is presented. The experimental setup consisted of a 137Cs radioactive source, a Geiger-Müller detector, and a radiation counter. Soil samples with four distinct granulometric compositions were analyzed. Strong linear correlations were found between the transmitted gamma-ray photon intensity and θ (correlation coefficients varying from −0.95 to −0.98). The soil porosity, measured by the conventional and GRA methods, presented differences that varied from c. 7.8% to c. 18.2%. In addition, strong linear relationships (correlation coefficients from 0.90 to 0.98) were observed between the GRA and the traditional (gravimetric) method of θ measurement. It was verified that the teaching GRA apparatus is useful for measuring θ. In addition, the apparatus allows the introduction of some important aspects related to the study of modern physics for undergraduate students of many fields of knowledge.
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Wei, Guiwu, Jianping Lu, Cun Wei, and Jiang Wu. "Probabilistic linguistic GRA method for multiple attribute group decision making." Journal of Intelligent & Fuzzy Systems 38, no. 4 (2020): 4721–32. http://dx.doi.org/10.3233/jifs-191416.
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Kolhapure, Rakesh, Vasudev Shinde, and Vijay Kamble. "Geometrical optimization of strain gauge force transducer using GRA method." Measurement 101 (April 2017): 111–17. http://dx.doi.org/10.1016/j.measurement.2017.01.030.
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廖, 健龙. "Progress of Slope Stability Research Based on FAHP-GRA Method." Hans Journal of Civil Engineering 14, no. 03 (2025): 391–98. https://doi.org/10.12677/hjce.2025.143045.
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Li, Li, and Li Jiu Wang. "Modified Method in Group Comparison Matrixes Consistency Check and its Application in Building Material Evaluation." Key Engineering Materials 477 (April 2011): 425–31. http://dx.doi.org/10.4028/www.scientific.net/kem.477.425.
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The comparison matrixes are obtained from decision makers might be contradictory, moreover an modified check method is proposed. Grey relational analysis (GRA) is adopted in group comparison matrixes consistency check for the first time. Firstly, the consistency indicators are put forward and are defined the definitions depending on GRA. Secondly, adjustment model is proposed to solve the group comparison matrixes inconsistency. Finally, the modified consistency check method are application in building material evaluation. It is believed that the proposed method is applicable to check consistency of building material evaluation.
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Sheng, Jie, Jihong Sun, Yongliang Bai, et al. "Evaluation of hydrocarbon potential using fuzzy AHP-based grey relational analysis: a case study in the Laoshan Uplift, South Yellow Sea, China." Journal of Geophysics and Engineering 17, no. 1 (2019): 189–202. http://dx.doi.org/10.1093/jge/gxz107.
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Abstract Effective evaluations of hydrocarbon potential contribute to delineating promising target areas for further exploration. Sparse available data and known hydrocarbon reservoirs in frontier areas present considerable challenges to the weighting of geological factors when evaluating hydrocarbon potential. This study proposes a hydrocarbon potential mapping method that employs grey relational analysis (GRA) based on a fuzzy analytic hierarchy process (fuzzy AHP). GRA is a comprehensive evaluation method that represents the hydrocarbon favourability according to the proximity between evaluation targets and the ideal target based on multiple evaluation factors and weights among them. To overcome the uncertainty and vagueness in the weighting procedure, the fuzzy AHP technique relies on experts’ knowledge to define the relative importance of evaluation factors and exploits triangular fuzzy numbers to simulate experts’ judgements in pairwise comparisons. The fuzzy AHP-based GRA method was tested using an example in the Laoshan Uplift in the South Yellow Basin of China. This test application not only quantified the favourability of local traps but also revealed their spatial variations on favourability maps and indicated potential targets for further exploration. The results obtained by the fuzzy AHP-based GRA method were more reliable than that of entropy weight-based GRA and displayed a suitable consistency with known geological information, thus demonstrating that such a procedure could reveal the potential spatial features of hydrocarbon accumulations and support the evaluation of hydrocarbon potential in relatively unknown areas.
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Joshi, Dr Manuj. "Multi-Criteria Decision-Making GRA Approach for Selecting Appropriate Classification Algorithm in Software Defect Prediction Systems." International Journal for Research in Applied Science and Engineering Technology 13, no. 3 (2025): 1352–58. https://doi.org/10.22214/ijraset.2025.67536.
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Grey Relational Analysis (GRA) is a powerful Multi-Criteria Decision-Making (MCDM) method used to evaluate and rank classification algorithms based on their performance in software defect prediction. This study applies GRA to multiple datasets, including AR1, JM1, and CM1, to assess the effectiveness of different classifiers in identifying software defects. The analysis considers various performance criteria, such as accuracy, computational efficiency, and scalability, to determine the most suitable classification algorithm. The results indicate that classifiers like Lazy-IBK and Misc-HyperPipes consistently achieve higher GRA scores, demonstrating their superior predictive capability. The findings validate the significance of GRA in selecting the optimal classification model, highlighting its role in enhancing decision-making in software defect prediction.
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Ayağ, Zeki, and Funda Samanlioglu. "Fuzzy AHP-GRA approach to evaluating energy sources: a case of Turkey." International Journal of Energy Sector Management 14, no. 1 (2020): 40–58. http://dx.doi.org/10.1108/ijesm-09-2018-0012.
Full textAbstract:
Purpose Since the demand for energy has dramatically increased in the countries which have fast-growing population and economy, they have faced with a critical problem of how to evaluate a set of potential energy sources (i.e. nuclear, natural gas, bio, geothermal, hydro, wind and solar) and choose the ultimate energy source for their needs. On the other hand, this critical problem turns into a multiple-criteria decision-making (MCDM) in the presence of a set of energy source alternatives and evaluation criteria. In literature, there are many MCDM methods introduced to solve for different kinds of problems. The purpose of this paper is to present an integrated approach for evaluating energy sources using fuzzy AHP and GRA, with a case for Turkey. Design/methodology/approach In this paper, the analytic hierarchy process (AHP) and grey relational analysis (GRA) methods are used because of their advantages for similar problems. On the other hand, due to the fact that the conventional AHP by a nine-point scale and GRA method using a scale with crisp values can be unable to handle to capture the right judgments of a decision-maker(s), to reflect the vagueness and uncertainty on the judgments of a decision-maker, the fuzzy logic is integrated with the AHP and GRA. Findings The contributions of the paper to the literature are given in two dimensions as follows: it presents an integrated approach for complex decision processes with subjective data or vague information; the proposed approach, the fuzzy AHP-GRA method for energy source selection, is unique for the related problem in literature. The results of the proposed model from the case of Turkey will help practitioners and experts of how to apply it to the similar problems in the field of energy management. Research limitations/implications In short, in this paper, an integrated approach is proposed through the fuzzy AHP and the fuzzy GRA methods. As the fuzzy AHP is used to determine the weights of evaluation criteria, the fuzzy GRA is used to rank energy source alternatives. Practical implications In addition, a case study for Turkey is presented to show the applicability of the proposed approach for potential practitioners who are authority in the field of energy in public and private sectors. Social implications On the other hand, the proposed approach, the fuzzy AHP-GRA for energy source selection can also be an intelligent tool for public and private energy companies in Turkey, as well as others in the world. Originality/value On the other hand, in this paper, to the best of the authors’ knowledge, the study contributes to the literature that the first time, they use the fuzzy alpha-cut AHP and GRA in fuzzy environment for energy source evaluation problem.