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Journal articles on the topic 'Fuzzy source information'

Author: Grafiati

Published: 4 June 2025

Last updated: 1 August 2025

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1

Wang, Hong, and Hong Li. "Uncertainty Measure for Multisource Intuitionistic Fuzzy Information System." Complexity 2022 (April 7, 2022): 1–21. http://dx.doi.org/10.1155/2022/3605881.

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Multisource information systems and multigranulation intuitionistic fuzzy rough sets are important extended types of Pawlak’s classical rough set model. Multigranulation intuitionistic fuzzy rough sets have been investigated in depth in recent years. However, few studies have considered this combination of multisource information systems and intuitionistic fuzzy rough sets. In this paper, we give the uncertainty measure for multisource intuitionistic fuzzy information system. Against the background of multisource intuitionistic fuzzy information system, each information source is regarded as a

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2

Zhang, Yun, and Chaoxia Qin. "A Gaussian-Shaped Fuzzy Inference System for Multi-Source Fuzzy Data." Systems 10, no. 6 (2022): 258. http://dx.doi.org/10.3390/systems10060258.

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Fuzzy control theory has been extensively used in the construction of complex fuzzy inference systems. However, we argue that existing fuzzy control technologies focus mainly on the single-source fuzzy information system, disregarding the complementary nature of multi-source data. In this paper, we develop a novel Gaussian-shaped Fuzzy Inference System (GFIS) driven by multi-source fuzzy data. To this end, we first propose an interval-value normalization method to address the heterogeneity of multi-source fuzzy data. The contribution of our interval-value normalization method involves mapping

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Zhang, Jin Fang, Hou Jin Chen, and Lei Fan. "Fuzzy Logic and Classification of Information Sources." Applied Mechanics and Materials 614 (September 2014): 378–80. http://dx.doi.org/10.4028/www.scientific.net/amm.614.378.

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Classic information theory is based on the probability information which isn't involved in any fuzzy events. A hypothesis of transformation and classification of uncertain information sources presented in this paper is exploited to explain several phenomena in information retrieval. First, the form of uncertainty is introduced including fuzzy and random. Then an information source containing a sample space and a fuzzy set is supposed to illustrate the hypothesis based on which a method of identification for information sources is educed. And there are also some problems for further study, such

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Luo, Jin, and Qi Bin Deng. "Application of Uncertain Information Fusion in Diagnosis Decision of Electronic Equipment." Applied Mechanics and Materials 341-342 (July 2013): 715–18. http://dx.doi.org/10.4028/www.scientific.net/amm.341-342.715.

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Focuses on how to dispose the multi-source uncertain information and promote the testability evaluation and fault diagnosis capability of the electronic equipment, this paper uses fuzzy theory in the uncertain information description and modeling. Based on the fuzzy set description of fuzzy target, new method is proposed to obtain fuzzy evidences from fuzzy fault features, and then, Dempster-Shafer combination rule are used to fuse multi-source fuzzy evidence to get diagnosis results. The proposed method of fuzzy evidence extraction can reduces uncertainties in fusion makings and improves faul

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Lin, Guoping, Jiye Liang, Yuhua Qian, and Jinjin Li. "A fuzzy multigranulation decision-theoretic approach to multi-source fuzzy information systems." Knowledge-Based Systems 91 (January 2016): 102–13. http://dx.doi.org/10.1016/j.knosys.2015.09.022.

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Xu, Weihua, Mengmeng Li, and Xizhao Wang. "Information Fusion Based on Information Entropy in Fuzzy Multi-source Incomplete Information System." International Journal of Fuzzy Systems 19, no. 4 (2016): 1200–1216. http://dx.doi.org/10.1007/s40815-016-0230-9.

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Zhang, Pengfei, Yuxin Zhao, Dexian Wang, Yujie Zhang, and Zheng Yu. "Fuzzy Rough Set Models Based on Fuzzy Similarity Relation and Information Granularity in Multi-Source Mixed Information Systems." Mathematics 12, no. 24 (2024): 4039. https://doi.org/10.3390/math12244039.

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As a pivotal research method in the field of granular computing (GrC), fuzzy rough sets (FRSs) have garnered significant attention due to their successful overcoming of the limitations of traditional rough sets in handling continuous data. This paper is dedicated to exploring the application potential of FRS models within the framework of multi-source complex information systems, which undoubtedly holds profound research significance. Firstly, a novel multi-source mixed information system (MsMIS), encompassing five distinct data types, is introduced, thereby enriching the dimensions of data pr

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Jiang, Ping, Yuzhen Wang, and Aidong Ge. "Multivariable Fuzzy Control Based Mobile Robot Odor Source Localization via Semitensor Product." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/736720.

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In order to take full advantage of the multisensor information, a MIMO fuzzy control system based on semitensor product (STP) is set up for mobile robot odor source localization (OSL). Multisensor information, such as vision, olfaction, laser, wind speed, and direction, is the input of the fuzzy control system and the relative searching strategies, such as random searching (RS), nearest distance-based vision searching (NDVS), and odor source declaration (OSD), are the outputs. Fuzzy control rules with algebraic equations are given according to the multisensor information via STP. Any output ca

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Nguyen, Hoa, Nguyen Thi Uyen Nhi, and Le Nhat Duy. "FUZZY RELATIONAL DATABASE MODEL AND MANAGEMANT SYSTEM FOR IMPRECISE INFORMATION." Journal of Computer Science and Cybernetics 37, no. 2 (2021): 145–62. http://dx.doi.org/10.15625/1813-9663/37/2/15346.

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This paper introduces a fuzzy relational database model (FRDB) and the management system for it. FRDB is built by extending the classical relational database model with the fuzzy membership degree of tuples in relations. The management system for FRDB with the querying language like SQL is built by using a classical open-source management system.

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GARRIDO, CARMEN, NICOLÁS MARÍN, and OLGA PONS. "FUZZY INTERVALS TO REPRESENT FUZZY VALID TIME IN A TEMPORAL RELATIONAL DATABASE." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 17, supp01 (2009): 173–92. http://dx.doi.org/10.1142/s021848850900608x.

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Temporal databases offer a common framework to those database applications that need to store or handle different types of temporal data from a variety of sources. They allow the concept of time to be handled from the point of view of meaning, representation, and manipulation. Although at first sight the incorporation of time into a database might appear to be a direct and simple task, it is, however, quite complex: not only must new structures and specific operators be included, but the semantics of conventional DML sentences (insert, update, or delete) and queries must be appropriately chang

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SU, Hong-Sheng. "Multi-source Fuzzy Information Fusion Method Based on Bayesian Optimal Classifier." Acta Automatica Sinica 34, no. 3 (2008): 282–87. http://dx.doi.org/10.3724/sp.j.1004.2008.00282.

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12

Bai, Luyi, Nan Li, and Huilei Bai. "An integration approach of multi-source heterogeneous fuzzy spatiotemporal data based on RDF." Journal of Intelligent & Fuzzy Systems 40, no. 1 (2021): 1065–82. http://dx.doi.org/10.3233/jifs-201258.

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With the growing importance of the fuzzy spatiotemporal data in information application, there is an increasing need for researching on the integration method of multi-source heterogeneous fuzzy spatiotemporal data. In this paper, we first propose a fuzzy spatiotemporal RDF graph model based on RDF (Resource Description Framework) that proposed by the World Wide Web Consortium (W3C) to represent data in triples (subject, predicate, object). Secondly, we analyze and classify the related heterogeneous problems of multi-source heterogeneous fuzzy spatiotemporal data, and use the fuzzy spatiotempo

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Cardone, Barbara, and Ferdinando Di Martino. "Bit Reduced FCM with Block Fuzzy Transforms for Massive Image Segmentation." Information 11, no. 7 (2020): 351. http://dx.doi.org/10.3390/info11070351.

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A novel bit reduced fuzzy clustering method applied to segment high resolution massive images is proposed. The image is decomposed in blocks and compressed by using the fuzzy transform method, then adjoint pixels with same gray level are binned and the fuzzy c-means algorithm is applied on the bins to segment the image. This method has the advantage to be applied to massive images as the compressed image can be stored in memory and the runtime to segment the image are reduced. Comparison tests are performed with respect to the fuzzy c-means algorithm to segment high resolution images; the resu

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Ding, Xue Wen, Berthold Mahundi, Fei Yang, and Guang Quan Xu. "Image Fusion Using Wavelet Transform and Fuzzy Reasoning." Applied Mechanics and Materials 239-240 (December 2012): 1336–39. http://dx.doi.org/10.4028/www.scientific.net/amm.239-240.1336.

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The image fusion algorithm discussed in this paper which utilizes wavelet decomposition and fuzzy reasoning combines images from diverse imaging sensors into a single composite image. It first decomposed source images through wavelet transform, computed the extent of each source image’s contribution through fuzzy reasoning using the area feature of source images, and then fused the coefficients through weighted averaging with the extents of each source images’ contributions as the weight coefficients. Experimental results indicate the final composite image may have more complete information co

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Deng, Zhongliang, Shihao Tang, Xiwen Deng, Lu Yin, and Jingrong Liu. "A Novel Location Source Optimization Algorithm for Low Anchor Node Density Wireless Sensor Networks." Sensors 21, no. 5 (2021): 1890. http://dx.doi.org/10.3390/s21051890.

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Location information is one of the basic elements of the Internet of Things (IoT), which is also an important research direction in the application of wireless sensor networks (WSNs). Aiming at addressing the TOA positioning problem in the low anchor node density deployment environment, the traditional cooperative localization method will reduce the positioning accuracy due to excessive redundant information. In this regard, this paper proposes a location source optimization algorithm based on fuzzy comprehensive evaluation. First, each node calculates its own time-position distribute conditio

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Gomzov, Nikolay, and Konstantin Zolnikov. "Application of neural fuzzy classification in decision support systems." BIO Web of Conferences 145 (2024): 04017. http://dx.doi.org/10.1051/bioconf/202414504017.

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The article proposes a classification of fuzzy information about the terrain for solving problems in the fields of agriculture and forestry. This classification allows for a more accurate description and understanding of the characteristics of fuzzy information, which can be useful for decision-making under uncertainty. Special attention is given to the area of forest fire modeling using geographic information systems. A hybrid fuzzy network is proposed for classifying the parameters of the fire source and the environment to select the optimal analytical model.

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Rakhmatullaev, Marat, Sherbek Normatov, and Fayzi Bekkamov. "FUZZY RELATIONS BASED INTELLIGENT INFORMATION RETRIEVAL FOR DIGITAL LIBRARY USERS." ENVIRONMENT. TECHNOLOGIES. RESOURCES. Proceedings of the International Scientific and Practical Conference 2 (June 13, 2023): 80–83. http://dx.doi.org/10.17770/etr2023vol2.7218.

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It is known that today information and library systems are one of the main sources of information needs of the population and have many users. Information and library systems have a large amount of valuable information resources and information retrieval services have been established to allow users to find the necessary literature. We know that search engines take requests and return results they think are relevant. As a result, the user again faces the problem of finding what he needs among the many sources of information provided.Today, a number of information systems effectively use recomm

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18

Tian Jing, Yu Dan, Yu Bing, and Ma Shilong. "A Fuzzy Multi-Criteria Group Decision Making Model for Information Source Selection." INTERNATIONAL JOURNAL ON Advances in Information Sciences and Service Sciences 4, no. 6 (2012): 184–92. http://dx.doi.org/10.4156/aiss.vol4.issue6.22.

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Wei Hu, and Ou Li. "Diagnosis Decision of Belt Conveyor Based On Multiple Source Fuzzy Information Fusion." International Journal of Digital Content Technology and its Applications 7, no. 7 (2013): 603–10. http://dx.doi.org/10.4156/jdcta.vol7.issue7.71.

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Tian, Jing, Dan Yu, Bing Yu, and Shilong Ma. "A fuzzy TOPSIS model via chi-square test for information source selection." Knowledge-Based Systems 37 (January 2013): 515–27. http://dx.doi.org/10.1016/j.knosys.2012.09.010.

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21

Sailaubekova, A. Zh, A. D. Zolotov, and E. A. Ospanov. "IMPROVING THE QUALITY OF REGULATION BY AVIATION EQUIPMENT WITH FUZZY SOURCE INFORMATION." Вестник Академии гражданской авиации, no. 3 (2022): 63–68. http://dx.doi.org/10.53364/24138614_2022_26_3_63.

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Wu, Bo, Bang Yan Ye, Chun Ling Wu, and Cheng Zhong Zhang. "Irrigation Water Compensation Control System Based on Fuzzy Neural Network." Advanced Materials Research 108-111 (May 2010): 1386–91. http://dx.doi.org/10.4028/www.scientific.net/amr.108-111.1386.

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This paper presents a Fuzzy Neural Network-based irrigation water control system for realizing accurate irrigation and water saving. The control system consists of a PC based server with a FNN-based control module, data sampling device, CAN bus communication network and remote irrigation units with sensors and controller. It can estimate irrigation water compensation according to the irrigation environments. By using Fuzzy Logic function and Fuzzy Neural Network, the controller module can fuse multi-source information that from Internet, sensors and other sources to make decision of irrigation

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Sirbiladze, Gia, Teimuraz Manjafarashvili, Bidzina Midodashvili, Bezhan Ghvaberidze, and David Mikadze. "Representation of a Crisp Set as a Pair of Dual Fuzzy Sets." Advances in Artificial Intelligence and Machine Learning 02, no. 04 (2022): 477–500. http://dx.doi.org/10.54364/aaiml.2022.1133.

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Expert knowledge representations often fail to determine compatibility levels on all objects, and these levels are represented for a certain sampling of universe. The samplings for the fuzzy terms of the linguistic variable, whose compatibility functions are aggregated according to a certain problem, may also be different. In such a case, neither L.A. Zadeh’s analysis of fuzzy sets and even the dual forms of developing today R.R. Yager’s q-rung orthopair fuzzy sets cannot provide the necessary aggregations. This fact, as a given, can be considered as a source of new types of information, in or

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Mert, Ali. "Defuzzification of Non-Linear Pentagonal Intuitionistic Fuzzy Numbers and Application in the Minimum Spanning Tree Problem." Symmetry 15, no. 10 (2023): 1853. http://dx.doi.org/10.3390/sym15101853.

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In recent years, with the variety of digital objects around us becoming a source of information, the fields of artificial intelligence (AI) and machine learning (ML) have experienced very rapid development. Processing and converting the information around us into data within the framework of the information processing theory is important, as AI and ML techniques need large amounts of reliable data in the training and validation stages. Even though information naturally contains uncertainty, information must still be modeled and converted into data without neglecting this uncertainty. Mathemati

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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.

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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 kind

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Guth, Johanna, Sven Wursthorn, and Sina Keller. "Multi-Parameter Estimation of Average Speed in Road Networks Using Fuzzy Control." ISPRS International Journal of Geo-Information 9, no. 1 (2020): 55. http://dx.doi.org/10.3390/ijgi9010055.

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Average speed is crucial for calculating link travel time to find the fastest path in a road network. However, readily available data sources like OpenStreetMap (OSM) often lack information about the average speed of a road. However, OSM contains other road information which enables an estimation of average speed in rural regions. In this paper, we develop a Fuzzy Framework for Speed Estimation (Fuzzy-FSE) that employs fuzzy control to estimate average speed based on the parameters road class, road slope, road surface and link length. The OSM road network and, optionally, a digital elevation m

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Saeed, Sima, and Aliakbar Niknafs. "Artificial Bee Colony-Fuzzy Q Learning for Reinforcement Fuzzy Control (Truck Backer-Upper Control Problem)." International Journal of Uncertainty, Fuzziness and Knowledge-Based Systems 24, no. 01 (2016): 123–36. http://dx.doi.org/10.1142/s0218488516500070.

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A new method for reinforcement fuzzy controllers is presented by this article. The method uses Artificial Bee Colony algorithm based on Q-Value to control reinforcement fuzzy system; the algorithm is called Artificial Bee Colony-Fuzzy Q learning (ABC-FQ). In fuzzy inference system, precondition part of rules is generated by prior knowledge, but ABC-FQ algorithm is responsible to achieve the best combination of actions for the consequence part of the rules. In ABC-FQ algorithm, each combination of actions is considered a food source for consequence part of the rules and the fitness level of thi

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Yadav, Nidhika, and Niladri Chatterjee. "Fuzzy Rough Set Based Technique for User Specific Information Retrieval." International Journal of Rough Sets and Data Analysis 5, no. 4 (2018): 32–47. http://dx.doi.org/10.4018/ijrsda.2018100102.

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Information retrieval is widely used due to extremely large volume of text and image data available on the web and consequently, efficient retrieval is required. Text information retrieval is a branch of information retrieval which deals with text documents. Another key factor is the concern for a retrieval engine, often referred to as user-specific information retrieval, which works according to a specific user. This article performs a preliminary investigation of the proposed fuzzy rough sets-based model for user-specific text information retrieval. The model improves on the computational ti

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Yang, Lei, Xiaoyan Zhang, Weihua Xu, and Binbin Sang. "Multi-granulation Rough Sets and Uncertainty Measurement for Multi-source Fuzzy Information System." International Journal of Fuzzy Systems 21, no. 6 (2019): 1919–37. http://dx.doi.org/10.1007/s40815-019-00667-1.

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Xia, Yuanpu, Ziming Xiong, Hao Lu, Zhu Wen, and Chao Ma. "Fuzzy risk assessment of a deeply buried tunnel under incomplete information." Royal Society Open Science 5, no. 10 (2018): 180305. http://dx.doi.org/10.1098/rsos.180305.

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Risk assessment has always been an important part of safety risk research in tunnel and underground engineering. Owing to the characteristics of tunnel construction, to achieve an expected risk control effect, it is necessary to carry out accurate risk assessment research according to the risk assessment concept based on the entire tunnel construction process. At present, because of the frequent occurrences of safety accidents, a variety of risk assessment models have been proposed for different tunnel projects such as subways and railway tunnels, which can be roughly classified into two types

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López-González, E., M. A. Rodríguez-Fernández, and C. Mendaña-Cuervo. "The logistic decision making in management accounting with genetic algorithms and fuzzy sets." Mathware & Soft Computing VII, no. 2-3 (2000): 229–41. https://doi.org/10.5281/zenodo.5076231.

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<strong>Abstract</strong> The logistics problems in business environments deal with assignation from a number of sources to a number of destinations. Each source offers amounts of goods, while each destination demands quantities of these goods. The object is to find the cheapest transporting schedule that satisfies the demand without violating supply restraints. In this paper we propose to use Fuzzy Sets to represent the previsional information related to costs, demands and other variables. Moreover, we suggest including the problem of shortest route for the distribution vehicles. Finally, to

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Du, Jian, Bao Jun Fei, Ying Liu, and Guo Zheng Yao. "Research on Reliability Assessment for the Armored Equipment Based on Multi-Source Information Fusion." Advanced Materials Research 760-762 (September 2013): 2091–94. http://dx.doi.org/10.4028/www.scientific.net/amr.760-762.2091.

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In order to solve the problem of reliability evaluation for armored equipment, used Bayes fusion theory, combined with minimal amounts of reliability information on the field test, the paper fusioned reliability information of the same model for armored equipment, and completed the reliability assessment for a certain type of armored equipment. The test results show that the technology of multi-source information fusion can effectively solve the fusion problem of the prior fuzzy information and small sample test data, improve the accuracy of the reliability assessment, prove the feasibility an

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Kułacz, Łukasz, and Adrian Kliks. "Dynamic Spectrum Allocation Using Multi-Source Context Information in OpenRAN Networks." Sensors 22, no. 9 (2022): 3515. http://dx.doi.org/10.3390/s22093515.

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Bearing in mind the stringent problem of limited and inefficiently used radio resources, a multi-source mechanism for the dynamic adjustment of occupied frequency bands is proposed. Instead of relying only on radio-related information, the system that collects data from various sources is discussed. Mainly, using the ubiquitous sources of information about the presence of users (such as city monitoring), it is possible to identify areas that have high or low expected traffic with high probabilities. Consequently, in low-traffic areas, it is not necessary to allocate all available spectrum reso

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Zhang, Xueyang, Xiaohong Chen, Xudong Lin, Jing Wang, and Jianqiang Wang. "Towards a Hybrid Evaluation Approach to Chinese Sustainable Drinking Water Source Regions within an Uncertain Decision Environment." Symmetry 12, no. 8 (2020): 1303. http://dx.doi.org/10.3390/sym12081303.

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Confronted with the increasingly serious water pollution in China, companies are implementing scientific measures to strive for sustainable drinking water source regions (DWSRs). The challenge lies in how to evaluate available DWSRs. Considering the complexity and uncertainty existing in the evaluation process, we deem this process a complicated multi-criteria group decision-making (MCGDM) problem. It involves fuzzy decision information, prioritized relationships among different criteria, and distinctively allocated weights of decision makers regarding different alternatives. By utilizing the

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Liu, Xinglong, Wei He, Xiumin Chu, Feng Ma, and Yang Nie. "A Multi-source Information Fusion Method for Error AIS Targets Identification." Open Electrical & Electronic Engineering Journal 8, no. 1 (2014): 729–37. http://dx.doi.org/10.2174/1874129001408010729.

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Automatic Identification System (AIS) is ship navigation equipment. Due to the fact that data-link guarantee mechanism has not been fully resolved, AIS sometimes broadcasts error messages and confused the marine administrators and sailors, so it’s important to automatically identify the error messages. In this paper, we proposed an error AIS messages identification framework, which based on prior probability, expert assessment, fuzzy membership degree and Dempster- Shafer’s (DS) evidence combining rule. In the framework, ship speed, course and longitude-latitude position are core indexes to ev

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HUANG, CHONGFU. "AN APPROACH TO ANALYZE RISKS BY COMPUTING WITH WORDS." New Mathematics and Natural Computation 07, no. 01 (2011): 89–103. http://dx.doi.org/10.1142/s1793005711001822.

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The information coded in natural language is called natural language information. It can be employed to analyze risks by computing with words. The disjunction and Cartesian product of fuzzy sets are the basic arithmetics to compute a probability distribution representing the random uncertainty of the risk source. An approach to infer a risk with words is to represent the risk system by using probabilistic and possibilistic constraints. In this paper, with fuzzy logic, we give a sample to verify that the suggested approach is more flexible and effective.

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Serhii, Semenov, Sira Oksana, Gavrylenko Svitlana, and Kuchuk Nina. "IDENTIFICATION OF THE STATE OF AN OBJECT UNDER CONDITIONS OF FUZZY INPUT DATA." Eastern-European Journal of Enterprise Technologies 1, no. 4 (97) (2019): 22–30. https://doi.org/10.15587/1729-4061.2019.157085.

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The modernization of the methods for identification of the state of objects under conditions of fuzzy input data, described by their membership functions, was performed. The selected direction of improvement of traditional methods is associated with the fundamental features of solving this problem under actual conditions of a small source data sample. Under these conditions, to solve the problem of state identification, it is advisable to transfer to the technology of description of source data, based on the mathematical apparatus of fuzzy mathematics and less demanding in terms of information

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Kumaraswamy, Suda, Dammavalam Srinivasa Rao, and Nuthanapati Naveen Kumar. "Satellite image fusion using fuzzy logic." Acta Universitatis Sapientiae, Informatica 8, no. 2 (2016): 241–53. http://dx.doi.org/10.1515/ausi-2016-0011.

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Abstract Image fusion is a method of combining the Multispectral (MS) and Panchromatic (PAN) images into one image contains more information than any of the input. Image fusion aim is to decrease unknown and weaken common data in the fused output image at the same time improving necessary information. Fused images are helpful in various applications like, remote sensing, computer vision, biometrics, change detection, image analysis and image classification. Conventional fusion methods are having some side effects like assertive spatial information and uncertain color information is an usually

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Attaullah, Shahzaib Ashraf, Noor Rehman, Asghar Khan, and Choonkil Park. "A decision making algorithm for wind power plant based on q-rung orthopair hesitant fuzzy rough aggregation information and TOPSIS." AIMS Mathematics 7, no. 4 (2022): 5241–74. http://dx.doi.org/10.3934/math.2022292.

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<abstract><p>Wind energy is one of the most significant renewable energy sources due to its widespread availability, low environmental impact, and great cost-effectiveness. The effective design of ideal wind energy extraction areas to generate electricity is one of the most critical issues in the exploitation of wind energy. The appropriate site selection for wind power plants is based on the concepts and criteria of sustainable environmental advancement, resulting in a low-cost and renewable energy source, as well as cost-effectiveness and job creation. The aim of this article is

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Wang, Ning, and Fei Zhao. "An Assessment of the Condition of Distribution Network Equipment Based on Large Data Fuzzy Decision-Making." Energies 13, no. 1 (2020): 197. http://dx.doi.org/10.3390/en13010197.

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As one of the most important components of power grid, a distribution network is the most vulnerable part in the face of various uncertainties, and influences the stability and economy of a power system. In this paper, the operational information, hardware information and human factors were considered, and a state evaluation model of multi-source information fusion was established. Based on big data fuzzy iteration method and a weighted expert library, a weighted distribution of multi-source information was obtained, and an equipment condition assessment was carried out reasonably. Taking the

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Ziquan, Xiang, Yang Jiaqi, Muhammad Hamza Naseem, and Xiang Zuquan. "Occupational Health and Safety Risk Assessment of Cruise Ship Construction Based on Improved Intuitionistic Fuzzy TOPSIS Decision Model." Mathematical Problems in Engineering 2021 (August 28, 2021): 1–13. http://dx.doi.org/10.1155/2021/5966711.

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The logistics of cruise ship construction are complex, with an extended period, many participants, and a stringent node control. The resulting occupational health and safety risks have more risks and uncertainties. If it is not identified and controlled, it will lead to low efficiency of logistics management in the construction stage, leading to chain breaking and going out of control. In response to this situation, this article proposes an improved intuitionistic fuzzy TOPSIS decision model to evaluate occupational health and safety risks in cruise ship construction. First, based on field res

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Polekhina, K. A., and G. Eu Polekhina. "Modeling financial market dynamics with the use of fuzzy." Vestnik Universiteta, no. 7 (August 31, 2024): 170–80. http://dx.doi.org/10.26425/1816-4277-2024-7-170-180.

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In the modern world, financial markets play an important role in the economy and people’s lives. They provide access to financial resources and are also a source of profit for many companies. However, instability in the financial markets can lead to serious consequences such as financial crises and loss of investor confidence. In this regard, modelling the financial market dynamics becomes increasingly relevant. This work considered the use of fuzzy mathematics for this purpose. Fuzzy mathematics is a branch of mathematics that studies methods and algorithms for dealing with fuzzy data and fuz

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Petrov, M. B., L. A. Serkov, and K. B. Kozhov. "Assessment of Energy Supply to the Yamal Peninsula Based on Fuzzy Multicriteria Analysis." Economy of Region 18, no. 4 (2022): 1209–22. http://dx.doi.org/10.17059/ekon.reg.2022-4-17.

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Provision of useful energy is the most important condition for realising the potential of underdeveloped regions. For new development areas, including the Yamal Peninsula, there are various energy alternatives. Based on well-known basic approaches, the article presents a procedure for formalising the analysis of alternatives mostly using qualitative initial data. At the pre-project stage, only limited and fuzzy information (predominantly in the form of expert opinions) is accessible. To achieve the set goal, six criteria for export assessment were selected and further processed using fuzzy mul

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Joshi, Bhagawati, Navneet Joshi, and Alexander Gegov. "TOPSIS based Renewable-Energy-Source-Selection using Moderator Intuitionistic Fuzzy Set." International Journal of Mathematical, Engineering and Management Sciences 8, no. 5 (2023): 979–90. http://dx.doi.org/10.33889/ijmems.2023.8.5.056.

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Many criteria must be taken into account while selecting the best renewable energy source (RES), which necessitates a sophisticated multi-criteria decision-making (MCDM) procedure. Conflicting norms, as well as insufficient and inaccurate information, make this endeavour challenging. The theory of moderator intuitionistic fuzzy set (MIFS), a generalization of intuitionistic fuzzy sets (IFSs) has been developed to handle these uncertainties. The MIFS also helps to get a higher degree of precision in the uncertain behaviours due to the moderator parameter. In this paper, first some distance meas

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Masuma, Mammadovа. "METHODS FOR FUZZY DEMAND ASSESSMENT FOR IT SPECIALTIES." EUREKA: Physics and Engineering, no. 4 (July 31, 2019): 23–33. https://doi.org/10.21303/2461-4262.2019.00939.

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The rapid development of information technologies and their penetration into various spheres of human activity cause a sharply increased demand for IT specialists, in many countries of the world far exceeding the supply on them. High rates of technological transformation contribute to the diversification of the IT segment of the labor market, on the one hand, stimulate the disappearance of some and the emergence of new IT specialties, on the other. This creates a discrepancy between the structure of IT-related education and the labor market demand for IT specialists of the required profile and

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Kolodenkova, A. E., and S. S. Vereshchagina. "INTELLIGENT APPROACH FOR DIAGNOSIS ELECTRICAL EQUIPMENT OF INDUSTRIAL FACILITIES." Vestnik komp'iuternykh i informatsionnykh tekhnologii, no. 185 (November 2019): 37–45. http://dx.doi.org/10.14489/vkit.2019.11.pp.037-045.

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This paper is devoted to actual problem of ensuring of trouble-free functioning and a high level of fault tolerance of industrial facilities’ electrical equipment (EE) by diagnosing them during their operation. However, when diagnosing equipment, a number of challenges arise related to the following problems: a large number of monitored parameters, the presence of not only statistical information but the values of linguistic variables that are used by staff on duty, insufficient and incomplete input information. Proposed approach to diagnosing EE based on a composition of fuzzy cognitive model

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Yin, XueHong. "Construction of Student Information Management System Based on Data Mining and Clustering Algorithm." Complexity 2021 (May 18, 2021): 1–11. http://dx.doi.org/10.1155/2021/4447045.

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Data mining is a new technology developed in recent years. Through data mining, people can discover the valuable and potential knowledge hidden behind the data and provide strong support for scientifically making various business decisions. This paper applies data mining technology to the college student information management system, mines student evaluation information data, uses data mining technology to design student evaluation information modules, and digs out the factors that affect student development and the various relationships between these factors. Predictive assessment of knowled

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Kozlov, Oleksiy. "INFORMATION TECHNOLOGY FOR SYNTHESIS AND OPTIMIZATION OF FUZZY SYSTEMS RULE BASES." Management of Development of Complex Systems, no. 45 (March 1, 2021): 66–74. http://dx.doi.org/10.32347/2412-9933.2021.45.66-74.

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In the last two decades, intelligent computer systems based on fuzzy set theory, fuzzy logic and soft computing are widely used in various fields of science and technology to solve problems of control, identification, modeling of complex physical and economic phenomena, classification, pattern recognition, etc. Modern research in the field of creation and development of fuzzy systems (FS) of control and decision-making is conducted mainly in the direction of development of highly effective methods and information technologies of their synthesis and structural-parametric optimization. This pape

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Su, Zilong, Hengzhen Feng, Fei Zhao, and Weikun Xuan. "Acousto-optic Multi-source Information Fusion Algorithm for Outdoor Pedestrian Detection." Journal of Physics: Conference Series 2478, no. 6 (2023): 062007. http://dx.doi.org/10.1088/1742-6596/2478/6/062007.

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Abstract The inefficiency of traditional rescue methods is a serious threat to the life and health of outdoor people in distress, so the research on pedestrian identification for outdoor rescue has important theoretical significance and application value. In order to solve the problem of low probability of recognition based on signal information in traditional methods, an outdoor pedestrian recognition model based on acousto-optic information fusion is constructed. Considering the characteristics of the information source, the directional gradient histogram of the infrared image and the Mel Ce

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Zhang, Ke, Tianhao Gao, and Huaitao Shi. "Bearing fault diagnosis method based on multi-source heterogeneous information fusion." Measurement Science and Technology 33, no. 7 (2022): 075901. http://dx.doi.org/10.1088/1361-6501/ac5deb.

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Abstract Bearing fault diagnosis is a critical component of the mechanical equipment monitoring system. In the complex and harsh environment in which bearings operate, the fault diagnosis approach of multi-source information fusion can extract fault features more stably and extensively than the traditional single-source fault diagnosis method. However, most existing multi-source fusion methods are in infancy, and there are a number of pressing issues to address, such as subjective elements having a significant impact, excessive data redundancy, fuzzy multi-source signal fusion strategy, and in

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