Relevant bibliographies by topics / Fuzzy Methods

Contents

  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers
  6. Reports

Academic literature on the topic 'Fuzzy Methods'

Author: Grafiati
Published: 10 March 2023
Last updated: 25 July 2025

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Journal articles on the topic "Fuzzy Methods"

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TAKAHAGI, Eiichiro. "Fuzzy Integrals and Fuzzy Reasoning Methods." Journal of Japan Society for Fuzzy Theory and Intelligent Informatics 27, no. 1 (2015): 12–19. http://dx.doi.org/10.3156/jsoft.27.1_12.

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Subbotin, Igor Ya, and Michael Gr Voskoglou. "Fuzzy Assessment Methods." Universal Journal of Applied Mathematics 2, no. 9 (2014): 305–11. http://dx.doi.org/10.13189/ujam.2014.020902.

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MIZUMOTO, Masaharu. "Fuzzy controls methods." Journal of the Robotics Society of Japan 6, no. 6 (1988): 528–35. http://dx.doi.org/10.7210/jrsj.6.6_528.

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Kumar, Amit, and Amarpreet Kaur. "Methods for Solving Fully Fuzzy Transportation Problems Based on Classical Transportation Methods." International Journal of Operations Research and Information Systems 2, no. 4 (2011): 52–71. http://dx.doi.org/10.4018/joris.2011100104.

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There are several methods, in literature, for finding the fuzzy optimal solution of fully fuzzy transportation problems (transportation problems in which all the parameters are represented by fuzzy numbers). In this paper, the shortcomings of some existing methods are pointed out and to overcome these shortcomings, two new methods (based on fuzzy linear programming formulation and classical transportation methods) are proposed to find the fuzzy optimal solution of unbalanced fuzzy transportation problems by representing all the parameters as trapezoidal fuzzy numbers. The advantages of the pro
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Perrone, G., and S. Noto La Diega. "Fuzzy methods for analysing fuzzy production environment." Robotics and Computer-Integrated Manufacturing 14, no. 5-6 (1998): 465–74. http://dx.doi.org/10.1016/s0736-5845(98)00021-0.

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Mizumoto, Masaharu. "Fuzzy controls under various fuzzy reasoning methods." Information Sciences 45, no. 2 (1988): 129–51. http://dx.doi.org/10.1016/0020-0255(88)90037-0.

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Ramzipoor, Roxanna. "Set theory and fuzzy sets: Their relationship to natural language." Qualitative & Multi-Method Research 12, no. 1 (2014): 9–14. https://doi.org/10.5281/zenodo.894606.

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An Interview with George Lakoff. Background: A recurring argument of scholars who advocate set theory and fuzzy sets for social science is that this frame-work is valuable and appropriate in part because it reflects the structure of meaning in natural language.2 George Lakoff has written extensively on these topics and is cited by these schol-ars as an authority. In this interview, Lakoff synthesizes a large body of research in linguistics and cognitive science, which contends that natural language is not set-theoretic in struc-ture. He also explores Lotfi Zadeh’s fuzzy logic, emphasizing both
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Uehara, Kiyohiko, and Kaoru Hirota. "A Fast Method for Fuzzy Rules Learning with Derivative-Free Optimization by Formulating Independent Evaluations of Each Fuzzy Rule." Journal of Advanced Computational Intelligence and Intelligent Informatics 25, no. 2 (2021): 213–25. http://dx.doi.org/10.20965/jaciii.2021.p0213.

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A method is proposed for evaluating fuzzy rules independently of each other in fuzzy rules learning. The proposed method is named α-FUZZI-ES (α-weight-based fuzzy-rule independent evaluations) in this paper. In α-FUZZI-ES, the evaluation value of a fuzzy system is divided out among the fuzzy rules by using the compatibility degrees of the learning data. By the effective use of α-FUZZI-ES, a method for fast fuzzy rules learning is proposed. This is named α-FUZZI-ES learning (α-FUZZI-ES-based fuzzy rules learning) in this paper. α-FUZZI-ES learning is especially effective when evaluation functio
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Ali, Fareed Jameel, H. Saleh Hafed, Azmi Amirah, Alomari Abedel-Karrem, Ratib Anakira Nidal, and Haji Man Noraziah. "Efficient approximate analytical methods for nonlinear fuzzy boundary value problem." International Journal of Electrical and Computer Engineering (IJECE) 12, no. 2 (2022): 1916–28. https://doi.org/10.11591/ijece.v12i2.pp1916-1928.

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This paper aims to solve the nonlinear two-point fuzzy boundary value problem (TPFBVP) using approximate analytical methods. Most fuzzy boundary value problems cannot be solved exactly or analytically. Even if the analytical solutions exist, they may be challenging to evaluate. Therefore, approximate analytical methods may be necessary to consider the solution. Hence, there is a need to formulate new, efficient, more accurate techniques. This is the focus of this study: two approximate analytical methods-homotopy perturbation method (HPM) and the variational iteration method (VIM) is proposed.
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Mahoney, James. "Reflections on fuzzy-set/QCA." Qualitative & Multi-Method Research 2, no. 2 (2004): 17–21. https://doi.org/10.5281/zenodo.998220.

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Ragin and Rihoux offer an informative overview of qualitative comparative analysis and its fuzzy-set extension (fs/QCA). They frame their discussion around three issues: (1) the distinctiveness of fs/QCA; (2) the state of the art; and (3) best practices. I will follow their lead by organizing this short note around these issues. However, whereas Ragin and Rihoux focus mostly on best practices, I will focus mostly on the distinctiveness of fs/QCA.
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Dissertations / Theses on the topic "Fuzzy Methods"

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Matthews, Chris, and mikewood@deakin edu au. "Fuzzy concepts and formal methods." Deakin University. School of Management Information Systems, 2001. http://tux.lib.deakin.edu.au./adt-VDU/public/adt-VDU20051201.154843.

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It has been recognised that formal methods are useful as a modelling tool in requirements engineering. Specification languages such as Z permit the precise and unambiguous modelling of system properties and behaviour. However some system problems, particularly those drawn from the information systems problem domain, may be difficult to model in crisp or precise terms. It may also be desirable that formal modelling should commence as early as possible, even when our understanding of parts of the problem domain is only approximate. This thesis suggests fuzzy set theory as a possible representati
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Swartz, Andre Michael. "Methods for designing and optimizing fuzzy controllers." Thesis, Rhodes University, 2000. http://hdl.handle.net/10962/d1005226.

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We start by discussing fuzzy sets and the algebra of fuzzy sets. We consider some properties of fuzzy modeling tools. This is followed by considering the Mamdani and Sugeno models for designing fuzzy controllers. Various methods for using sets of data for desining controllers are discussed. This is followed by a chapter illustrating the use of genetic algorithms in designing and optimizing fuzzy controllers.Finally we look at some previous applications of fuzzy control in telecommunication networks, and illustrate a simple application that was developed as part of the present work.
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Prajitno, Prawito. "Neuro-fuzzy methods in multisensor data fusion." Thesis, University of Sheffield, 2002. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.251258.

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FURUHASHI, Takeshi, and Makoto YASUDA. "Fuzzy Entropy Based Fuzzy c-Means Clustering with Deterministic and Simulated Annealing Methods." Institute of Electronics, Information and Communication Engineers, 2009. http://hdl.handle.net/2237/15060.

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Wang, Yanfei. "Fuzzy methods for analysis of microarrays and networks." Thesis, Queensland University of Technology, 2011. https://eprints.qut.edu.au/48175/1/Yanfei_Wang_Thesis.pdf.

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Bioinformatics involves analyses of biological data such as DNA sequences, microarrays and protein-protein interaction (PPI) networks. Its two main objectives are the identification of genes or proteins and the prediction of their functions. Biological data often contain uncertain and imprecise information. Fuzzy theory provides useful tools to deal with this type of information, hence has played an important role in analyses of biological data. In this thesis, we aim to develop some new fuzzy techniques and apply them on DNA microarrays and PPI networks. We will focus on three problems: (1) c
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Abd, Rahim Noor Hafhizah. "Comparing and compressing fuzzy concepts : methods and application." Thesis, University of Bristol, 2015. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.682484.

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In recent years, the volume of data has risen so rapidly due to the Internet and World Wide Web development. This phenomenon called information overload or digital obesity has caused data explosion and may lead to storage problems in the future. Many forms of data are stored and transmitted via internet including textual data. Textual data, which is usually in unstructured form can be processed or mined to yield useful information. In order to represent that, we need to know the underlying concepts. The most suitable approach to model the concepts is to design an ontology. Formal Concept Analy
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Siddique, Muhammad. "Fuzzy decision making using max-min and MMR methods." Thesis, Blekinge Tekniska Högskola, Sektionen för ingenjörsvetenskap, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:bth-3042.

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Fuzzy logic is based on the theory of fuzzy sets, where an object’s membership of a set is gradual rather than just member or not a member. Fuzzy logic uses the whole interval of real numbers between zero (False) and one (True) to develop a logic as a basis for rules of inference. Particularly the fuzzified version of the modus ponens rule of inference enables computers to make decisions using fuzzy reasoning rather than exact. We study decision making problem under uncertainty. we analyze Max-Min method and Minimization of regret method originally developed by Savage and further developed by
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Nasser, Sara. "Fuzzy methods for meta-genome sequence classification and assembly." abstract and full text PDF (free order & download UNR users only), 2008. http://0-gateway.proquest.com.innopac.library.unr.edu/openurl?url_ver=Z39.88-2004&rft_val_fmt=info:ofi/fmt:kev:mtx:dissertation&res_dat=xri:pqdiss&rft_dat=xri:pqdiss:3307706.

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Eliason, Ryan Lee. "Application of Convex Methods to Identification of Fuzzy Subpopulations." BYU ScholarsArchive, 2010. https://scholarsarchive.byu.edu/etd/2242.

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In large observational studies, data are often highly multivariate with many discrete and continuous variables measured on each observational unit. One often derives subpopulations to facilitate analysis. Traditional approaches suggest modeling such subpopulations with a compilation of interaction effects. However, when many interaction effects define each subpopulation, it becomes easier to model membership in a subpopulation rather than numerous interactions. In many cases, subjects are not complete members of a subpopulation but rather partial members of multiple subpopulations. Grade of Me
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Kotta, Anwesh. "Condition Monitoring : Using Computational intelligence methods." Master's thesis, Universitätsbibliothek Chemnitz, 2015. http://nbn-resolving.de/urn:nbn:de:bsz:ch1-qucosa-187100.

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Machine tool components are widely used in many industrial applications. In accordance with their usage, a reliable health monitoring system is necessary to detect defects in these components in order monitor machinery performance and avoid malfunction. Even though several techniques have been reported for fault detection and diagnosis, it is a challenging task to implement a condition monitoring system in real world applications due to their complexity in structure and noisy operating environment. The primary objective of this thesis is to develop novel intelligent algorithms for a reliable f
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Books on the topic "Fuzzy Methods"

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Siegfried, Gottwald, ed. Fuzzy sets, fuzzy logic, fuzzy methods with applications. J. Wiley, 1995.

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Viertl, Reinhard. Statistical Methods for Fuzzy Data. John Wiley & Sons, Ltd, 2011. http://dx.doi.org/10.1002/9780470974414.

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Buckley, James J., and Leonard J. Jowers. Monte Carlo Methods in Fuzzy Optimization. Springer Berlin Heidelberg, 2008. http://dx.doi.org/10.1007/978-3-540-76290-4.

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J, Jowers Leonard, and SpringerLink (Online service), eds. Monte Carlo Methods in Fuzzy Optimization. Springer-Verlag Berlin Heidelberg, 2008.

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Keung, Lai Kin, and Wang Shouyang 1958-, eds. Fuzzy portfolio optimization: Theory and methods. Springer, 2008.

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1929-, Hwang C. L., ed. Fuzzy mathematical programming: Methods and applications. Springer-Verlag, 1992.

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Cao, Bing-Yuan. Optimal Models and Methods with Fuzzy Quantities. Springer-Verlag Berlin Heidelberg, 2010.

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Cao, Bing-Yuan. Optimal Models and Methods with Fuzzy Quantities. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-10712-2.

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Arfi, Badredine. Linguistic Fuzzy Logic Methods in Social Sciences. Springer Berlin Heidelberg, 2010. http://dx.doi.org/10.1007/978-3-642-13343-5.

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Kluska, Jasek. Analytical Methods in Fuzzy Modeling and Control. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-89927-3.

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Book chapters on the topic "Fuzzy Methods"

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Collette, Yann, and Patrick Siarry. "Fuzzy methods." In Multiobjective Optimization. Springer Berlin Heidelberg, 2004. http://dx.doi.org/10.1007/978-3-662-08883-8_4.

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Czogała, Ernest, and Jacek Łęski. "Unsupervised learning Clustering methods." In Fuzzy and Neuro-Fuzzy Intelligent Systems. Physica-Verlag HD, 2000. http://dx.doi.org/10.1007/978-3-7908-1853-6_4.

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Hatwagner, Miklós F. "Model Reduction Methods." In Fuzzy Cognitive Maps. Springer Nature Switzerland, 2023. http://dx.doi.org/10.1007/978-3-031-37959-8_5.

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Chen, Shu-Jen, and Ching-Lai Hwang. "Fuzzy Ranking Methods." In Lecture Notes in Economics and Mathematical Systems. Springer Berlin Heidelberg, 1992. http://dx.doi.org/10.1007/978-3-642-46768-4_4.

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Marsala, Christophe. "Fuzzy Partitioning Methods." In Granular Computing. Physica-Verlag HD, 2001. http://dx.doi.org/10.1007/978-3-7908-1823-9_8.

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El Alaoui, Mohamed. "Frequently Used Multicriteria Decision-Making Methods." In Fuzzy TOPSIS. CRC Press, 2021. http://dx.doi.org/10.1201/9781003168416-4-4.

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Dikopoulou, Zoumpolia. "Fuzzy Cognitive Maps." In Fuzzy Management Methods. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-81496-0_3.

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Diamond, Phil. "Least Squares Methods in Fuzzy Data Analysis." In Fuzzy Logic. Springer Netherlands, 1993. http://dx.doi.org/10.1007/978-94-011-2014-2_38.

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Mikut, Ralf, Jens Jäkel, and Lutz Gröll. "Inference Methods for Partially Redundant Rule Bases." In Fuzzy Control. Physica-Verlag HD, 2000. http://dx.doi.org/10.1007/978-3-7908-1841-3_13.

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Denzler, Alexander. "Introduction." In Fuzzy Management Methods. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-22978-8_1.

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Conference papers on the topic "Fuzzy Methods"

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Dimuro, Graçaliz Pereira, Helida Salles Santos, Asier Urio-Larrea, et al. "Grouping Indices: Definition, Properties and Construction Methods." In 2024 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2024. http://dx.doi.org/10.1109/fuzz-ieee60900.2024.10611928.

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Mikhailov, Dmitriy A., and Maxim V. Abramov. "Novel Optimization Methods for Fuzzy Networks." In 2025 XXVIII International Conference on Soft Computing and Measurements (SCM). IEEE, 2025. https://doi.org/10.1109/scm66446.2025.11060426.

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Boffa, Stefania, Carmen De Maio, Antonio Di Nola, Giuseppe Fenza, Anna Rita Ferraioli, and Vincenzo Loia. "Unifying fuzzy concept lattice construction methods." In 2016 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2016. http://dx.doi.org/10.1109/fuzz-ieee.2016.7737689.

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Parker, Jonathon K., Lawrence O. Hall, and James C. Bezdek. "Comparison of scalable fuzzy clustering methods." In 2012 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2012. http://dx.doi.org/10.1109/fuzz-ieee.2012.6250815.

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Granville, N. W. "Fuzzy analysis of fuzzy images." In IEE Colloquium Intelligent Methods in Healthcare and Medical Applications. IEE, 1998. http://dx.doi.org/10.1049/ic:19981034.

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PERFILIEVA, IRINA. "FUZZY NUMERICAL METHODS." In Proceedings of the 5th International FLINS Conference. WORLD SCIENTIFIC, 2002. http://dx.doi.org/10.1142/9789812777102_0007.

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Zhu, Xiaodong, Zhiqiu Huang, Shuqun Yang, and Guohua Shen. "Fuzzy Implication Methods in Fuzzy Logic." In Fourth International Conference on Fuzzy Systems and Knowledge Discovery (FSKD 2007). IEEE, 2007. http://dx.doi.org/10.1109/fskd.2007.327.

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Cross, Valerie V., Valeria Mokrenko, and Shangye Chen. "Comparing Similarity and Distance Based Fuzzy Inferencing Methods." In 2018 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2018. http://dx.doi.org/10.1109/fuzz-ieee.2018.8491584.

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Kupka, Jiri, and Pavel Rusnok. "On regression methods based on linguistic descriptions." In 2015 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2015. http://dx.doi.org/10.1109/fuzz-ieee.2015.7338040.

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Arias-Duart, Anna, Ferran Pares, Dario Garcia-Gasulla, and Victor Gimenez-Abalos. "Focus! Rating XAI Methods and Finding Biases." In 2022 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2022. http://dx.doi.org/10.1109/fuzz-ieee55066.2022.9882821.

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Reports on the topic "Fuzzy Methods"

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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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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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Kryzhanivs'kyi, Evstakhii, Liliana Horal, Iryna Perevozova, Vira Shyiko, Nataliia Mykytiuk, and Maria Berlous. Fuzzy cluster analysis of indicators for assessing the potential of recreational forest use. [б. в.], 2020. http://dx.doi.org/10.31812/123456789/4470.

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Cluster analysis of the efficiency of the recreational forest use of the region by separate components of the recreational forest use potential is provided in the article. The main stages of the cluster analysis of the recreational forest use level based on the predetermined components were determined. Among the agglomerative methods of cluster analysis, intended for grouping and combining the objects of study, it is common to distinguish the three most common types: the hierarchical method or the method of tree clustering; the K-means Clustering Method and the two-step aggregation method. For
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Rahimi, Noshad. Developing a Mixed-Methods Method to Model Elderly Health Technology Adoption with Fuzzy Cognitive Map, and its Application in Adoption of Remote Health Monitoring Technologies by Elderly Women. Portland State University Library, 2000. http://dx.doi.org/10.15760/etd.6395.

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Yusrina, Asri, Ulfah Alifia, Shintia Revina, Rezanti Putri Pramana, and Luhur Bima. Is the Game Worth the Candle? Examining the Effectiveness of Initial Teacher Education in Indonesia. Research on Improving Systems of Education (RISE), 2022. http://dx.doi.org/10.35489/bsg-rise-wp_2022/106.

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An impactful teacher education programme equips teachers with knowledge and skills to improve their effectiveness. Empirical findings on the effectiveness of teacher preparation programmes show that the accountability of institutions and teachers should not only be based on the knowledge or skills produced but also on student learning. Our study aims to evaluate the effectiveness of a pre-service teacher education programme in Indonesia, known as Pendidikan Profesi Guru Prajabatan or PPG. PPG is a one-year full-time programme in addition to four years of undergraduate teacher education (Bachel
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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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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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Berkman, Heather. Social Exclusion and Violence in Latin America and the Caribbean. Inter-American Development Bank, 2007. http://dx.doi.org/10.18235/0010983.

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This paper examines how social exclusion contributes to violence in communities throughout Latin America and the Caribbean. Residents in socially excluded communities cannot depend on those institutions designed to protect them, and violence becomes an instrument to achieve certain outcomes, such as justice, security, and economic gain. When conventional methods of obtaining and working for increased social status, higher income, and wider influence are limited, as they often are in marginalized areas, some feel compelled to resort to violent acts. This paper discusses how social exclusion and
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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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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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Osipov, Gennadij Sergeevich. The simplest method of solving a fuzzy linear problem EXCHANGE. КультИнформПресс, 2017. http://dx.doi.org/10.18411/spbcsa-2017-4.

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Bozhenyuk, Alexander V., Stanislav L. Belyakov, and Margarita V. Knyazeva. Method for Finding the Chromatic Number of Intuitionistic Fuzzy Graph. DOI CODE, 2023. http://dx.doi.org/10.18411/doicode-2023.214.

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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.

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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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