Готові списки джерел за темами / Fuzzy System Models

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  1. Статті в журналах
  2. Дисертації
  3. Книги
  4. Частини книг
  5. Тези доповідей конференцій
  6. Звіти організацій

Добірка наукової літератури з теми "Fuzzy System Models"

Автор: Grafiati
Опубліковано: 3 червня 2025
Оновлено: 31 липня 2025

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Статті в журналах з теми "Fuzzy System Models"

1

Hamdy, Abeer. "Genetic Fuzzy System for Enhancing Software Estimation Models." International Journal of Modeling and Optimization 4, no. 3 (2014): 227–32. http://dx.doi.org/10.7763/ijmo.2014.v4.378.

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2

Yakhyaeva, G. E. "Classes of Fuzzy Models." Bulletin of Irkutsk State University. Series Mathematics 51 (2025): 151–66. https://doi.org/10.26516/1997-7670.2025.51.151.

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Анотація:
The paper is devoted to research in the field of fuzzy model theory. The paper introduces the notion of a coordinated valuation of sentences of a given signature, which can be considered as a generalisation of the notion of a realizable set of sentences to the fuzzy case. By analogy with the classical case, classes of fuzzy models generated by coordinated valuations are considered, and the notion of axiomatised class of fuzzy models is introduced. Fuzzy truth values of different sentences can be considered as a formalisation of subjective evaluative knowledge of experts about object domain. To
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3

Celikyilmaz, A., and I. Burhan Turksen. "Enhanced Fuzzy System Models With Improved Fuzzy Clustering Algorithm." IEEE Transactions on Fuzzy Systems 16, no. 3 (2008): 779–94. http://dx.doi.org/10.1109/tfuzz.2007.905919.

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4

Kramer, Klaus-Dietrich, Annedore Söchting, and Thomas Stolze. "Fuzzy Control Teaching Models." Issues in Informing Science and Information Technology 13 (2016): 225–33. http://dx.doi.org/10.28945/3490.

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Анотація:
Many degree courses at technical universities include the subject of control systems engineering. As an addition to conventional approaches Fuzzy Control can be used to easily find control solutions for systems, even if they include nonlinearities. To support further educational training, models which represent a technical system to be controlled are required. These models have to represent the system in a transparent and easy cognizable manner. Furthermore, a programming tool is required that supports an easy Fuzzy Control development process, including the option to verify the results and tu
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5

FILEV, DIMITER. "SYSTEM APPROACH TO DYNAMIC FUZZY MODELS." International Journal of General Systems 21, no. 3 (1992): 311–37. http://dx.doi.org/10.1080/03081079208945084.

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6

Ziyadullaev, Davron, Dilnoz Muhamediyeva, Zafar Abdullaev, Sharofiddin Aynaqulov, and Khasanturdi Kayumov. "Generalized models of a production system of fuzzy conclusion." E3S Web of Conferences 365 (2023): 01019. http://dx.doi.org/10.1051/e3sconf/202336501019.

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Анотація:
The aim of the research is to study the models, rules, and fuzzy inference engines, which occupy the main place in the knowledgebase, and models of the logic inference engines and simulation modeling, focused on supporting the adoption of semi-structured decisions under uncertainty. This implies the relevance of the task of developing theoretical and methodological tools that provide automation of the processes of fuzzy inference systems. Research methods are the theory of fuzzy sets and fuzzy logic. New scientific results are the design and formation of a set of production rules from a given
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7

Thorndike, Alan M. "Fuzzy system models on an IBM PC." ACM SIGSMALL/PC Notes 14, no. 3 (1988): 10–22. http://dx.doi.org/10.1145/49473.49474.

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8

Türksen, I. B., and M. H. Fazel Zarandi. "Fuzzy system models for aggregate scheduling analysis." International Journal of Approximate Reasoning 19, no. 1-2 (1998): 119–43. http://dx.doi.org/10.1016/s0888-613x(98)10003-8.

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Zak, S. H. "Stabilizing fuzzy system models using linear controllers." IEEE Transactions on Fuzzy Systems 7, no. 2 (1999): 236–40. http://dx.doi.org/10.1109/91.755404.

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10

Jiang, Hang, Xin Wang, and Li Ming Wang. "Multiple Models Fuzzy PID Controller Design in Ship Power System." Applied Mechanics and Materials 672-674 (October 2014): 1558–61. http://dx.doi.org/10.4028/www.scientific.net/amm.672-674.1558.

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Анотація:
The ship power system is a complex system with time varying, nonlinear and strong coupling characters. The traditional PID controller is difficult to meet the requirements of the system.In this paper, a multiple models fuzzy PID controller is designed. Considering the different operating conditions of on-land ship power system, two excitation regulation model which respectively corresponds to a fuzzy PID controller are set up. Each time, based on the input operation condition tested, only one fuzzy PID Controller is chosen to improve the control precision. At the end, simulation results show t
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Дисертації з теми "Fuzzy System Models"

1

Hu, Cheng Lin. "Design optimization of fuzzy models in system identification." Thesis, University of Macau, 2010. http://umaclib3.umac.mo/record=b2493501.

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2

Xu, Li Da. "Fuzzy multiobjective mathematical programming in economic systems analysis: design and method." PDXScholar, 1986. https://pdxscholar.library.pdx.edu/open_access_etds/471.

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Анотація:
Economic systems analysis is a systems analysis technique of setting out the factors that have to be taken into account in making economic systems decisions. The inquiring and operational systems of the technique are almost exclusively designed for well-structured systems. In review of economic systems analysis against systems thinking, there is a growing tendency to discard the analytical approach as inappropriate for dealing with an ill-structured issue. Therefore, economic systems analysis needs both the inquiring and operational systems which are appropriate for ill-structured systems. The
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3

Zaidi, Salman [Verfasser]. "System Identification of Stochastic Nonlinear Dynamic Systems using Takagi-Sugeno Fuzzy Models / Salman Zaidi." Kassel : Kassel University Press, 2019. http://d-nb.info/118450279X/34.

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4

Ngo, Darius. "Fault diagnosis in a system where information is poor." Thesis, University of Oxford, 1999. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.300725.

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5

Renners, Ingo. "Data-driven system identification via evolutionary retrieval of Takagi-Sugeno fuzzy models." [S.l. : s.n.], 2004. http://deposit.ddb.de/cgi-bin/dokserv?idn=974452351.

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6

Ozelkan, Ertunga Cem 1970. "Multi-objective fuzzy regression applied to the calibration of conceptual rainfall-runoff models." Diss., The University of Arizona, 1997. http://hdl.handle.net/10150/282486.

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Анотація:
The purpose of this research is (1) to develop a multi-objective fuzzy regression (MOFR) tool to overcome the shortcomings of the existing fuzzy regression approaches while keeping the good characteristics, and (2) to study systems with uncertain elements, using the example of rainfall-runoff process to illustrate the approach. Previous research has shown that fuzzy regression performs superior compared to statistical regression in some cases. On the other hand, fuzzy regression has also been criticized because it does not allow all data points to influence the estimated parameters, it is sens
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7

Akkapeddi, Alekhya. "Activity Monitoring System for Early Illness Detection in Independent Living Elders using Fuzzy Models." University of Cincinnati / OhioLINK, 2018. http://rave.ohiolink.edu/etdc/view?acc_num=ucin1522412674542829.

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8

Meza, Bustamante Katherine Isabel. "The creation of tools and models to characterize and quantify user-centered design considerations in product and system development." Orlando, Fla. : University of Central Florida, 2008. http://purl.fcla.edu/fcla/etd/CFE0002178.

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Ullah, Noor. "ANFIS BASED MODELS FOR ACCESSING QUALITY OF WIKIPEDIA ARTICLES." Thesis, Högskolan Dalarna, Datateknik, 2010. http://urn.kb.se/resolve?urn=urn:nbn:se:du-4909.

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Анотація:
Wikipedia is a free, web-based, collaborative, multilingual encyclopedia project supported by the non-profit Wikimedia Foundation. Due to the free nature of Wikipedia and allowing open access to everyone to edit articles the quality of articles may be affected. As all people don’t have equal level of knowledge and also different people have different opinions about a topic so there may be difference between the contributions made by different authors. To overcome this situation it is very important to classify the articles so that the articles of good quality can be separated from the poor qua
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Hwang, Yuan-Chun. "Local and personalised models for prediction, classification and knowledge discovery on real world data modelling problems." Click here to access this resource online, 2009. http://hdl.handle.net/10292/776.

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Анотація:
This thesis presents several novel methods to address some of the real world data modelling issues through the use of local and individualised modelling approaches. A set of real world data modelling issues such as modelling evolving processes, defining unique problem subspaces, identifying and dealing with noise, outliers, missing values, imbalanced data and irrelevant features, are reviewed and their impact on the models are analysed. The thesis has made nine major contributions to information science, includes four generic modelling methods, three real world application systems that apply t
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Книги з теми "Fuzzy System Models"

1

1953-, Pedrycz Witold, ed. Fuzzy modelling: Paradigms and practice. Kluwer Academic Publishers, 1996.

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2

Angelov, Plamen P. Evolving rule-based models: A tool for design of flexible adaptive systems. Physica-Verlag, 2002.

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3

I, Ruban A., ed. Imitat͡s︡ionnye modeli neopredelennykh sistem. VO ʺNaukaʺ, 1993.

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4

Nelles, Oliver. Nonlinear System Identification: From Classical Approaches to Neural Networks and Fuzzy Models. Springer Berlin Heidelberg, 2001.

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5

Ledeneva, T. M. Modelirovanie prot︠s︡essa agregirovanii︠a︡ informat︠s︡ii v t︠s︡elenapravlennykh sistemakh. Voronezhskiĭ gos. tekhnicheskiĭ universitet, 1999.

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6

Jamshidi, Mohammad. Large-scale systems: Modeling, control, and fuzzy logic. Prentice Hall, 1997.

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7

Angelov, Plamen P. Evolving Rule-Based Models: A Tool for Design of Flexible Adaptive Systems. Physica-Verlag HD, 2002.

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8

M, Welch Ronald, and United States. National Aeronautics and Space Administration., eds. Global single and multiple cloud classification with a fuzzy logic expert system. National Aeronautics and Space Administration, 1996.

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9

Kortunov, A. I. Annotirovannai︠a︡ khronika voennoĭ sluzhby narodov Urala v XVI-XIX vv. RIT︠S︡ BashGU, 2009.

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10

Chernichovsky, Dov. A fuzzy logic approach toward solving the analytic maze of health system financing. National Bureau of Economic Research, 2001.

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Частини книг з теми "Fuzzy System Models"

1

Nelles, Oliver. "Fuzzy and Neuro-Fuzzy Models." In Nonlinear System Identification. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04323-3_11.

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2

Nelles, Oliver. "Fuzzy and Neuro-Fuzzy Models." In Nonlinear System Identification. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47439-3_12.

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3

Nelles, Oliver. "Dynamic Neural and Fuzzy Models." In Nonlinear System Identification. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04323-3_17.

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4

Nelles, Oliver. "Dynamic Neural and Fuzzy Models." In Nonlinear System Identification. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47439-3_21.

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5

Wang, Shuming, and Junzo Watada. "System Reliability Optimization Models with Fuzzy Random Lifetimes." In Fuzzy Stochastic Optimization. Springer US, 2012. http://dx.doi.org/10.1007/978-1-4419-9560-5_4.

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6

Nelles, Oliver. "Local Linear Neuro-Fuzzy Models: Fundamentals." In Nonlinear System Identification. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04323-3_12.

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7

Nelles, Oliver. "Dynamic Local Linear Neuro-Fuzzy Models." In Nonlinear System Identification. Springer Berlin Heidelberg, 2001. http://dx.doi.org/10.1007/978-3-662-04323-3_18.

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8

Nelles, Oliver. "Local Linear Neuro-Fuzzy Models: Fundamentals." In Nonlinear System Identification. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47439-3_13.

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9

Nelles, Oliver. "Dynamic Local Linear Neuro-Fuzzy Models." In Nonlinear System Identification. Springer International Publishing, 2020. http://dx.doi.org/10.1007/978-3-030-47439-3_22.

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10

Türkşen, I. Burhan. "Fuzzy System Models Evolution from Fuzzy Rulebases to Fuzzy Functions." In Encyclopedia of Complexity and Systems Science Series. Springer US, 2009. http://dx.doi.org/10.1007/978-1-0716-2628-3_239.

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Тези доповідей конференцій з теми "Fuzzy System Models"

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Shi, Kuo, Jie Lu, Zhen Fang, and Guangquan Zhang. "Enhancing Vision-Language Models Incorporating TSK Fuzzy System for Domain Adaptation." In 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2024. http://dx.doi.org/10.1109/fuzz-ieee60900.2024.10612077.

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2

Chikhalikar, Akash, Ankit A. Ravankar, Jose Victorio Salazar Luces, and Yasuhisa Hirata. "Open Vocabulary Object Search Utilizing Large Language Models and Fuzzy Inferencing." In 2025 IEEE/SICE International Symposium on System Integration (SII). IEEE, 2025. https://doi.org/10.1109/sii59315.2025.10870891.

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3

Xinyue, Quan, Zhang Yao, Xie Xiang, and Wang Ya. "An Interview System Based on Large Language Models and Multi-Agent Interactions." In 2024 20th International Conference on Natural Computation, Fuzzy Systems and Knowledge Discovery (ICNC-FSKD). IEEE, 2024. http://dx.doi.org/10.1109/icnc-fskd64080.2024.10702317.

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4

Rahem, Hakima, Rabah Mellah, and Massinissa Zidane. "Implementation of The Neuro-fuzzy Controller for Delayed Position-Position Teleoperation System Using Arduino Due Board." In 2024 28th International Conference on Methods and Models in Automation and Robotics (MMAR). IEEE, 2024. http://dx.doi.org/10.1109/mmar62187.2024.10680763.

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5

S.Subhakar, Ch Jyothi Swaroop, P.Bharath, and Ch.Kumar. "Decision Support System for predicting crop yield using ARIMA, SARIMA and fuzzy logic models." In 2025 IEEE International Conference on Interdisciplinary Approaches in Technology and Management for Social Innovation (IATMSI). IEEE, 2025. https://doi.org/10.1109/iatmsi64286.2025.10985334.

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6

Raman, Ramakrishnan, Vikram Kumar, Biju G. Pillai, Apurv Verma, Shailesh Rastogi, and Meenakshi. "Development of Fuzzy Based Models for Detection System with More Accuracy for the Implementation of Healthcare/Clinical System." In 2024 4th International Conference on Advance Computing and Innovative Technologies in Engineering (ICACITE). IEEE, 2024. http://dx.doi.org/10.1109/icacite60783.2024.10617150.

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7

Kramer, Klaus-Dietrich, Annedore Söchting, and Thomas Stolze. "Fuzzy Control Teaching Models." In InSITE 2016: Informing Science + IT Education Conferences: Lithuania. Informing Science Institute, 2016. http://dx.doi.org/10.28945/3422.

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Анотація:
Many degree courses at technical universities include the subject of control systems engineering. As an addition to conventional approaches Fuzzy Control can be used to easily find control solutions for systems, even if they include nonlinearities. To support further educational training, models which represent a technical system to be controlled are required. These models have to represent the system in a transparent and easy cognizable manner. Furthermore, a programming tool is required that supports an easy Fuzzy Control development process, including the option to verify the results and tu
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8

Zeng, Xiao-Jun. "A comparison between T-S fuzzy systems and affine T-S fuzzy systems as nonlinear control system models." In 2014 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2014. http://dx.doi.org/10.1109/fuzz-ieee.2014.6891856.

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9

Silva, Hyago R. M., Rodrigo Cardim, Marcelo C. M. Teixeira, Edvaldo Assuncao, and Igor T. M. Ramos. "Switched Control and Tracking Application in Aeropendulum System using Fuzzy Models." In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2021. http://dx.doi.org/10.1109/fuzz45933.2021.9494543.

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Mikaeilvand, Nasser, Tofigh Allahviranloo, Alberto Cabada, Eduardo Liz, and Juan J. Nieto. "Solutions of The Fully Fuzzy Linear System." In MATHEMATICAL MODELS IN ENGINEERING, BIOLOGY AND MEDICINE: International Conference on Boundary Value Problems: Mathematical Models in Engineering, Biology and Medicine. AIP, 2009. http://dx.doi.org/10.1063/1.3142938.

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Звіти організацій з теми "Fuzzy System Models"

1

Seale, Maria, R. Salter, Natàlia Garcia-Reyero,, and Alicia Ruvinsky. A fuzzy epigenetic model for representing degradation in engineered systems. Engineer Research and Development Center (U.S.), 2022. http://dx.doi.org/10.21079/11681/45582.

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Анотація:
Degradation processes are implicated in a large number of system failures, and are crucial to understanding issues related to reliability and safety. Systems typically degrade in response to stressors, such as physical or chemical environmental conditions, which can vary widely for identical units that are deployed in different places or for different uses. This situational variance makes it difficult to develop accurate physics-based or data-driven models to assess and predict the system health status of individual components. To address this issue, we propose a fuzzy set model for representi
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2

Tsidylo, Ivan M., Serhiy O. Semerikov, Tetiana I. Gargula, Hanna V. Solonetska, Yaroslav P. Zamora, and Andrey V. Pikilnyak. Simulation of intellectual system for evaluation of multilevel test tasks on the basis of fuzzy logic. CEUR Workshop Proceedings, 2021. http://dx.doi.org/10.31812/123456789/4370.

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Анотація:
The article describes the stages of modeling an intelligent system for evaluating multilevel test tasks based on fuzzy logic in the MATLAB application package, namely the Fuzzy Logic Toolbox. The analysis of existing approaches to fuzzy assessment of test methods, their advantages and disadvantages is given. The considered methods for assessing students are presented in the general case by two methods: using fuzzy sets and corresponding membership functions; fuzzy estimation method and generalized fuzzy estimation method. In the present work, the Sugeno production model is used as the closest
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3

Buyak, Bogdan B., Ivan M. Tsidylo, Victor I. Repskyi, and Vitaliy P. Lyalyuk. Stages of Conceptualization and Formalization in the Design of the Model of the Neuro-Fuzzy Expert System of Professional Selection of Pupils. [б. в.], 2018. http://dx.doi.org/10.31812/123456789/2669.

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Анотація:
The article describes the problem of designing a neuro-fuzzy expert system of professional selection at the stages of conceptualization and formalization, which involves the definition of concepts, relationships and management mechanisms necessary to describe the solution of problems in the chosen subject field. The structural model of the decision making system for determining the professional selection of students for training in IT specialties is substantiated. Three subsystems are proposed as structural components for studying: psychological peculiarities, personal qualities, factual knowl
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4

Raychev, Nikolay. Hybrid system with fuzzy hierarchical evaluation model. Web of Open Science, 2020. http://dx.doi.org/10.37686/nal.v1i1.40.

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5

Blake, Carolyn, Benjamin P. Rigby, Roxanne Armstrong-Moore, et al. Participatory systems mapping for population health research, policy and practice: guidance on method choice and design. University of Glasgow, 2024. http://dx.doi.org/10.36399/gla.pubs.316563.

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Анотація:
What is participatory systems mapping? Participatory systems mapping engages stakeholders with varied knowledge and perspectives in creating a visual representation of a complex system. Its purpose is to explore, and document perceived causal relations between elements in the system. This guidance focuses on six causal systems mapping methods: systems-based theory of change maps; causal loop diagrams; CECAN participatory systems mapping; fuzzy cognitive maps; systems dynamics models; and Bayesian belief networks. What is the purpose of this guidance? This guidance includes a Framework that aid
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6

Karam, Sofia, Morteza Nagahi, Vidanelage Dayarathna, Junfeng Ma, Raed Jaradat, and Michael Hamilton. Integrating systems thinking skills with multi-criteria decision-making technology to recruit employee candidates. Engineer Research and Development Center (U.S.), 2021. http://dx.doi.org/10.21079/11681/41026.

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Анотація:
The emergence of modern complex systems is often exacerbated by a proliferation of information and complication of technologies. Because current complex systems challenges can limit an organization's ability to efficiently handle socio-technical systems, it is essential to provide methods and techniques that count on individuals' systems skills. When selecting future employees, companies must constantly refresh their recruitment methods in order to find capable candidates with the required level of systemic skills who are better fit for their organization's requirements and objectives. The pur
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Kucherova, Hanna, Anastasiia Didenko, Olena Kravets, Yuliia Honcharenko, and Aleksandr Uchitel. Scenario forecasting information transparency of subjects' under uncertainty and development of the knowledge economy. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4469.

Повний текст джерела
Анотація:
Topicality of modeling information transparency is determined by the influence it has on the effectiveness of management decisions made by an economic entity in the context of uncertainty and information asymmetry. It has been found that information transparency is a poorly structured category which acts as a qualitative characteristic of information and at certain levels forms an additional spectrum of properties of the information that has been adequately perceived or processed. As a result of structuring knowledge about the factor environment, a fuzzy cognitive model of information transpar
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8

Lavrentieva, Olena O., Ihor O. Arkhypov, Olexander I. Kuchma, and Aleksandr D. Uchitel. Use of simulators together with virtual and augmented reality in the system of welders’ vocational training: past, present, and future. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/3748.

Повний текст джерела
Анотація:
The article discusses the theory and methods of simulation training, its significance in the context of training specialists for areas where the lack of primary qualification is critical. The most widespread hardware and software solutions for the organization welders' simulation training that use VR- and AR- technologies have been analyzed. A review of the technological infrastructure and software tools for the virtual teaching-and-production laboratory of electric welding has been made on the example of the achievements of Fronius, MIMBUS, Seabery. The features of creating a virtual simulati
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