Relevant bibliographies by topics / Fuzzy rule based methods

Contents

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

Academic literature on the topic 'Fuzzy rule based methods'

Author: Grafiati
Published: 4 June 2025
Last updated: 15 July 2025

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Journal articles on the topic "Fuzzy rule based methods"

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Su, Pan, and Xueying Ren. "Fuzzy Rule Interpolation Methods Based on Sparse Rule Bases." International Journal of Computer Science and Information Technology 5, no. 3 (2025): 83–91. https://doi.org/10.62051/ijcsit.v5n3.08.

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Fuzzy rule interpolation algorithms have broad applications in computational fuzzy inference systems. This paper systematically introduces interpolation methods based on α-cuts. It focuses on two classical α-cut-based interpolation methods: the KH fuzzy rule interpolation method and the Lagrange fuzzy rule interpolation method. Through theoretical analysis and comparative studies, the fundamental principles, performance characteristics, and limitations of these two interpolation algorithms are explored in depth. Based on this, a fuzzy inference system for the "tip calculation problem" was cons
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Daniachew, Adeola Azy, Averey Barack Clevon, Abimelech Keita Avram, and Dodavah Tesseman Chislon. "Hybrid Grid Partition and Rought Set Methods for Generating Fuzzy Rules in Data Set Classification." International Journal of Enterprise Modelling 13, no. 3 (2019): 156–73. http://dx.doi.org/10.35335/emod.v13i3.73.

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This research aims to address the issue of exponential rule generation in fuzzy rule-based classification systems by developing a hybrid grid partition and rough set method. Fuzzy rule-based classification systems have the potential to construct linguistically understandable models, but a major constraint is the significant increase in the number of rules with a high number of attributes, which can diminish interpretation and classification accuracy. In this study, the grid partition method is utilized to generate fuzzy rules with adaptively adjusted grid structures, thus avoiding exponential
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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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Jin, Shangzhu. "A Bidirectional Reasoning Based on Fuzzy Interpolation." International Journal of Software Science and Computational Intelligence 12, no. 1 (2020): 1–14. http://dx.doi.org/10.4018/ijssci.2020010101.

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In order to deal with both the “curse of dimensionality” and the “sparse rule base” simultaneously, an initial idea of hierarchical bidirectional fuzzy interpolation is presented in this article, combining hierarchical fuzzy systems and forward/backward fuzzy rule interpolation. In particular, backward fuzzy interpolation can be employed to allow interpolation to be carried out when certain antecedents of observation variables are absent, whereas conventional methods do not work. Hierarchical bidirectional fuzzy interpolation is applicable to situations where a multiple multi-antecedent rules
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CHEN, SHYI-MING, YU-CHUAN CHANG, ZE-JIN CHEN, and CHIA-LING CHEN. "MULTIPLE FUZZY RULES INTERPOLATION WITH WEIGHTED ANTECEDENT VARIABLES IN SPARSE FUZZY RULE-BASED SYSTEMS." International Journal of Pattern Recognition and Artificial Intelligence 27, no. 05 (2013): 1359002. http://dx.doi.org/10.1142/s0218001413590027.

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This paper presents a new method for multiple fuzzy rules interpolation with weighted antecedent variables in sparse fuzzy rule-based systems based on polygonal membership functions. First, the proposed method calculates the normalized weighting vector of each closest fuzzy rule. Then, it calculates the composite weight of each closest fuzzy rule. Then, it calculates the left normal point [Formula: see text] and the right normal point [Formula: see text] of the fuzzy interpolative reasoning result [Formula: see text], respectively. Finally, it calculates the characteristic points [Formula: see
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Zhivitskaya, E. N., and T. A. Safronova. "Project Quality Assessment Based on Fuzzy Nodeling." Digital Transformation, no. 2 (August 6, 2019): 5–12. http://dx.doi.org/10.38086/2522-9613-2019-2-5-12.

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Methods for decision making as semi-structured goals which based on creation of linguistic model are considered in this article. Pattern of fuzzy model system is presented. Creation fuzzy model for project quality with substantive interpretation for input (projector experience, universality, projector error bar, project complexity, quality of basic data, engineering time) and output (project error) variables is reported in main body. Rule blokes are indicated to estimate output variable. The first rule bloke – projector rating- consists of 36 fuzzy rules that help taking into account quality o
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Uehara, Kiyohiko, Shun Sato, and Kaoru Hirota. "Inference for Nonlinear Mapping with Sparse Fuzzy Rules Based on Multi-Level Interpolation." Journal of Advanced Computational Intelligence and Intelligent Informatics 15, no. 3 (2011): 264–87. http://dx.doi.org/10.20965/jaciii.2011.p0264.

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An inference method is proposed for sparse fuzzy rules on the basis of interpolations at a number of points determined by α-cuts of given facts. The proposed method can perform nonlinear mapping even with sparse rule bases when each given fact activates a number of fuzzy rules which represent nonlinear relations. The operations for the nonlinear mapping are exactly the same as for the case when given facts activate no fuzzy rules due to the sparseness of rule bases. Such nonlinear mapping cannot be provided by conventional methods for sparse fuzzy rules. In evaluating the proposed method, mean
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Alcala-Fdez, Jesus, Rafael Alcala, Sergio Gonzalez, Yusuke Nojima, and Salvador Garcia. "Evolutionary Fuzzy Rule-Based Methods for Monotonic Classification." IEEE Transactions on Fuzzy Systems 25, no. 6 (2017): 1376–90. http://dx.doi.org/10.1109/tfuzz.2017.2718491.

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Li, Zhi Gang, and Feng Li Yang. "The Generation of the Fuzzy Control Rules Based on Association Rules with Temporal Constraints." Applied Mechanics and Materials 385-386 (August 2013): 931–34. http://dx.doi.org/10.4028/www.scientific.net/amm.385-386.931.

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In the field of fuzzy control, the generation of fuzzy control rules has always been a problem, because the industrial data is generally expressed in the order of time ,so it strongly depends on the time, it does not take the factors of temporal constraints into account in the previous extracting rule process.This paper uses temporal constraint association rule ,and uses the data mining methods to generate temporal fuzzy control rules. The method is verified by using the MATLAB7.1 ,the simulation shows that the method can achieve good fuzzy control rules.
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Aria, Jozi, Pinto Tiago, Praça Isabel, Silva Francisco, Teixeira Brigida, and Vale Zita. "Genetic fuzzy rule-based system using MOGUL learning methodology for energy consumption forecasting." Advances in Distributed Computing and Artificial Intelligence Journal 8, no. 1 (2020): 55–64. https://doi.org/10.14201/ADCAIJ2019815564.

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This paper presents the application of a Methodology to Obtain Genetic fuzzy rulebased systems Under the iterative rule Learning approach (MOGUL) to forecast energy consumption. Historical data referring to the energy consumption gathered from three groups, namely lights, HVAC and electrical socket, are used to train the proposed approach and achieve forecasting results for the future. The performance of the proposed method is compared to that of previous approaches, namely Hybrid Neural Fuzzy Interface System (HyFIS) and Wang and Mendel’s Fuzzy Rule Learning Method (WM). Results show th
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Dissertations / Theses on the topic "Fuzzy rule based methods"

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Karmakar, Gour Chandra 1970. "An integrated fuzzy rule-based image segmentation framework." Monash University, Gippsland School of Computing and Information Technology, 2002. http://arrow.monash.edu.au/hdl/1959.1/8752.

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Cruz, Anderson Paiva. "On Fuzzy Implication Classes - Towards Extensions of Fuzzy Rule-Based Systems." Universidade Federal do Rio Grande do Norte, 2012. http://repositorio.ufrn.br:8080/jspui/handle/123456789/18684.

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Made available in DSpace on 2015-03-03T15:47:46Z (GMT). No. of bitstreams: 1 AndersonPC_DISSERT.pdf: 1402040 bytes, checksum: 960b15bc1392a94fb7ba8ba980e3a0b4 (MD5) Previous issue date: 2012-12-20<br>Coordena??o de Aperfei?oamento de Pessoal de N?vel Superior<br>Atualmente, h? diferentes defini??es de implica??es fuzzy aceitas na literatura. Do ponto de vista te?rico, esta falta de consenso demonstra que h? discord?ncias sobre o real significado de "implica??o l?gica" nos contextos Booleano e fuzzy. Do ponto de vista pr?tico, isso gera d?vidas a respeito de quais "operadores de implica
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Hawkins, M. E. "Fuzzy rule-based control of ducted air flows." Thesis, University of Oxford, 1993. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.334222.

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Arabikhan, Farzad. "Telecommuting choice modelling using fuzzy rule based networks." Thesis, University of Portsmouth, 2017. https://researchportal.port.ac.uk/portal/en/theses/telecommuting-choice-modelling-using-fuzzy-rule-based-networks(b088b779-8daa-441e-b0a0-7c9641e1f08b).html.

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Telecommuting as an approach in transportation demand management has made the news a lot in recent years. Technology has enabled this growing trend, and more and more companies and families are taking advantages of it. Adopting telecommuting is a multidimensional decision making process that involves different aspects of life such as family, work and many more. Modelling telecommuting enables employers and employees to understand the main factors that influence on decision making about adopting telecommuting. The role of subjective knowledge and linguistic variables cannot be ignored in human
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Baaj, Ismaïl. "Explainability of possibilistic and fuzzy rule-based systems." Electronic Thesis or Diss., Sorbonne université, 2022. http://www.theses.fr/2022SORUS021.

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Aujourd'hui, les progrès de l'Intelligence Artificielle (IA) ont conduit à l'émergence de systèmes capables d'automatiser des processus complexes, en utilisant des modèles qui peuvent être difficiles à comprendre par les humains. Lorsque les humains utilisent ces systèmes d'IA, il est bien connu qu'ils veulent comprendre leurs comportements et leurs actions, car ils ont davantage confiance dans les systèmes qui peuvent expliquer leurs choix, leurs hypothèses et leurs raisonnements. La capacité d'explication des systèmes d'IA est devenue une exigence des utilisateurs, en particulier dans les en
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Dan, Qing. "A fuzzy rule-based approach for edge feature classification." Thesis, National Library of Canada = Bibliothèque nationale du Canada, 1999. http://www.collectionscanada.ca/obj/s4/f2/dsk2/ftp03/MQ39646.pdf.

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Carse, Brian. "Artificial evolution of fuzzy and temporal rule based systems." Thesis, University of the West of England, Bristol, 1997. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.267551.

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Kim, Hantae. "FUZZY RULE-BASED RELAXATION SCHEMES IN GROUNDWATER FLOW COMPUTATIONS." Kyoto University, 1998. http://hdl.handle.net/2433/182424.

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Kyoto University (京都大学)<br>0048<br>新制・課程博士<br>博士(農学)<br>甲第7563号<br>農博第1024号<br>新制||農||772(附属図書館)<br>学位論文||H10||N3213(農学部図書室)<br>UT51-99-A249<br>京都大学大学院農学研究科農業工学専攻<br>(主査)教授 河地 利彦, 教授 青山 咸康, 教授 三野 徹<br>学位規則第4条第1項該当
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Sánchez-Martínez, Felipe. "Using unsupervised corpus-based methods to build rule-based machine translation systems." Doctoral thesis, Universidad de Alicante, 2008. http://hdl.handle.net/10045/13879.

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Tanscheit, Ricardo. "Study of a rule-based self-organising controller for robotics applications." Thesis, Queen Mary, University of London, 1988. http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.282802.

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Books on the topic "Fuzzy rule based methods"

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Li, Fangyi, and Qiang Shen. Fuzzy Rule-Based Inference. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-97-0491-0.

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Mendel, Jerry M. Uncertain Rule-Based Fuzzy Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51370-6.

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Mendel, Jerry M. Explainable Uncertain Rule-Based Fuzzy Systems. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-35378-9.

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Mendel, Jerry M. Uncertain rule-based fuzzy logic systems: Introduction and new directions. Prentice Hall, 2001.

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Ebrahimnejad, Ali, and José Luis Verdegay. Fuzzy Sets-Based Methods and Techniques for Modern Analytics. Springer International Publishing, 2018. http://dx.doi.org/10.1007/978-3-319-73903-8.

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Geyer-Schulz, Andreas. Fuzzy rule-based expert systems and genetic machine learning. Physica-Verlag, 1995.

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Bárdossy, András. Fuzzy rule-based modeling with applications to geophysical, biological, and engineering systems. CRC Press, 1995.

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Gonzalez, Claudia I., Patricia Melin, Juan R. Castro, and Oscar Castillo. Edge Detection Methods Based on Generalized Type-2 Fuzzy Logic. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-53994-2.

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

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B, Sidor L., United States. National Aeronautics and Space Administration. Scientific and Technical Information Branch., and Dryden Flight Research Facility, eds. Rule-based air combat simulation. National Aeronautics and Space Administration, Scientific and Technical Information Branch, 1988.

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Book chapters on the topic "Fuzzy rule based methods"

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Mendel, Jerry M. "Type-1 Fuzzy Systems: Design Methods and Applications." In Uncertain Rule-Based Fuzzy Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51370-6_4.

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Mendel, Jerry M. "Interval Type-2 Fuzzy Systems: Design Methods and Applications." In Uncertain Rule-Based Fuzzy Systems. Springer International Publishing, 2017. http://dx.doi.org/10.1007/978-3-319-51370-6_10.

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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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Mendel, Jerry M. "Type-1 Fuzzy Systems: Design Methods and Case Studies." In Explainable Uncertain Rule-Based Fuzzy Systems. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-35378-9_4.

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Mendel, Jerry M. "Interval Type-2 Fuzzy Systems: Design Methods and Case Studies." In Explainable Uncertain Rule-Based Fuzzy Systems. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-35378-9_10.

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Wang, Lipo, Feng Chu, and Wei Xie. "Fuzzy Logic and Rule-Based Methods in Bioinformatics." In Springer Handbook of Bio-/Neuroinformatics. Springer Berlin Heidelberg, 2014. http://dx.doi.org/10.1007/978-3-642-30574-0_15.

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Kluska, Jasek. "Fuzzy Rule-Based Systems with Polynomial Membership Functions." In Analytical Methods in Fuzzy Modeling and Control. Springer Berlin Heidelberg, 2009. http://dx.doi.org/10.1007/978-3-540-89927-3_4.

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Johanyák, Zsolt Csaba, and Olga Papp. "Benchmark Based Comparison of Two Fuzzy Rule Base Optimization Methods." In Applied Computational Intelligence in Engineering and Information Technology. Springer Berlin Heidelberg, 2012. http://dx.doi.org/10.1007/978-3-642-28305-5_7.

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Tusor, Balázs, János T. Tóth, and Annamária R. Várkonyi-Kóczy. "An Indexed Rule-Based Fuzzy Color Filtering Method." In Recent Advances in Intelligent Engineering. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-030-14350-3_15.

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Tsumoto, Shusaku, and Hiroshi Tanaka. "PRIMEROSE: Probabilistic Rule Induction Method Based on Rough Set Theory." In Rough Sets, Fuzzy Sets and Knowledge Discovery. Springer London, 1994. http://dx.doi.org/10.1007/978-1-4471-3238-7_33.

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Conference papers on the topic "Fuzzy rule based methods"

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Sturrock, C. P., and W. F. Bogaerts. "Computer Learning Systems in Corrosion." In CORROSION 1996. NACE International, 1996. https://doi.org/10.5006/c1996-96657.

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Abstract A collection of data documenting the stress corrosion cracking (SCC) behavior of austenitic stainless steels provides the basis for an automated learning system. Computer learning systems based on classical and non-parametric statistics, connectionist models, machine learning methods, and fuzzy logic are described. An original method for inducing fuzzy rules from input-output data is presented. All of these computer learning systems are used to solve a typical problem of corrosion engineering: determine the likelihood of SCC of austenitic stainless steels given varying conditions of t
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Guan, Yu. "Regularization Method for Rule Reduction in Belief Rule-based SystemRegularization Method for Rule Reduction in Belief Rule-based System." In 8th International Conference on Computational Science and Engineering (CSE 2020). AIRCC Publishing Corporation, 2020. http://dx.doi.org/10.5121/csit.2020.101705.

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Belief rule-based inference system introduces a belief distribution structure into the conventional rule-based system, which can effectively synthesize incomplete and fuzzy information. In order to optimize reasoning efficiency and reduce redundant rules, this paper proposes a rule reduction method based on regularization. This method controls the distribution of rules by setting corresponding regularization penalties in different learning steps and reduces redundant rules. This paper first proposes the use of the Gaussian membership function to optimize the structure and activation process of
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Li, C. James, Chong-suhk Lee, and Sun’an Wang. "Diagnosis and Diagnostic Rule Extraction Using Fuzzy Neural Network." In ASME 2001 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2001. http://dx.doi.org/10.1115/imece2001/dsc-24506.

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Abstract The goal of this study is to develop a reasoning device and a diagnostic rule extraction methodology based on fuzzy neural network. This paper describes a method to obtain a fuzzy neural network classifier from labeled training data sets and algorithms to extracted linguistic diagnostic rules from such a trained fuzzy neural network. Benchmark comparisons were performed using three data sets from three different fields of applications. The proposed methodology was shown to outperform all the existing methods that were compared.
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Gersnoviez, Andres, and Iluminada Baturone. "Rule Simplification Method Based on Covering Indexes for Fuzzy Classifiers." In 2021 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2021. http://dx.doi.org/10.1109/fuzz45933.2021.9494545.

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CHUDÁČEK, VACLAV, MILAN PETRíK, MICHAL HUPTYCH, and LENKA LHOTSKÁ. "FUZZY RULE BASED DECISION TREE CLASSIFICATION OF ECG HOLTER BEATS." In Proceedings of the 8th International Workshop on Mathematical Methods in Scattering Theory and Biomedical Engineering. WORLD SCIENTIFIC, 2008. http://dx.doi.org/10.1142/9789812814852_0027.

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Ciftcioglu, O. "Note on orthogonal transformation methods for simplifying fuzzy rule-based models." In IEEE Annual Meeting of the Fuzzy Information, 2004. Processing NAFIPS '04. IEEE, 2004. http://dx.doi.org/10.1109/nafips.2004.1337397.

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Balazs, Krisztian, Janos Botzheim, and Laszlo T. Koczy. "Comparative analysis of interpolative and non-interpolative fuzzy rule based machine learning systems applying various numerical optimization methods." In 2010 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2010. http://dx.doi.org/10.1109/fuzzy.2010.5584156.

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Sevakula, Rahul K., Abhi Shah, and Nishchal K. Verma. "Data preprocessing methods for Sparse Auto-encoder based fuzzy rule classifier." In 2015 IEEE Workshop on Computational Intelligence: Theories, Applications and Future Directions (WCI). IEEE, 2015. http://dx.doi.org/10.1109/wci.2015.7495516.

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Chua, TeckWee, and WoeiWan Tan. "A new fuzzy rule-based initialization method for K-Nearest neighbor classifier." In 2009 IEEE International Conference on Fuzzy Systems (FUZZ-IEEE). IEEE, 2009. http://dx.doi.org/10.1109/fuzzy.2009.5277215.

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Ishibuchi, H. "Fuzzy reasoning method in fuzzy rule-based systems with general and specific rules for function approximation." In Proceedings of 8th International Fuzzy Systems Conference. IEEE, 1999. http://dx.doi.org/10.1109/fuzzy.1999.793234.

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Reports on the topic "Fuzzy rule based 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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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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Paule, Bernard, Flourentzos Flourentzou, Tristan de KERCHOVE d’EXAERDE, Julien BOUTILLIER, and Nicolo Ferrari. PRELUDE Roadmap for Building Renovation: set of rules for renovation actions to optimize building energy performance. Department of the Built Environment, 2023. http://dx.doi.org/10.54337/aau541614638.

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In the context of climate change and the environmental and energy constraints we face, it is essential to develop methods to encourage the implementation of efficient solutions for building renovation. One of the objectives of the European PRELUDE project [1] is to develop a "Building Renovation Roadmap"(BRR) aimed at facilitating decision-making to foster the most efficient refurbishment actions, the implementation of innovative solutions and the promotion of renewable energy sources in the renovation process of existing buildings. In this context, Estia is working on the development of infer
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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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Pinzón-Puerto, Freddy, and Mauricio Villamizar-Villegas. Do Actions Speak Louder than Words? A Foreign Exchange Intervention Analysis. Banco de la República Colombia, 2023. http://dx.doi.org/10.32468/be.1223.

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We revisit an old question but with a new identification strategy, namely the difference in exchange rate effects between announced (“vocal”) and secret (“dirty”) foreign exchange intervention. Using a Regression Discontinuity Design, we exploit a rule-based intervention mechanism enacted by the Central Bank of Colombia that, under observable and deterministic conditions, triggered either the issuance of FX options or the ability to exercise them. We take the former (issuance) as central bank announcements under a sharp setting, since the rule and information that triggered the issuance of opt
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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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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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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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VandeVusse, Alicia, Jennifer Mueller, Madeleine Haas, Priscille Osias, and Tamrin Ann Tchou. Publicly Supported Family Planning Clinics in 2022–2023: Trends in Service Delivery Practices and Protocols. Guttmacher Institute, 2024. http://dx.doi.org/10.1363/2024.300607.

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Key Points Publicly supported family planning clinics play a crucial role in the health care system, providing essential contraceptive services to millions of people every year. These safety-net clinics have faced several obstacles since 2015, such as the Title X domestic gag rule, the COVID-19 pandemic and the overturning of Roe v. Wade. The proportion of clinics offering a wide range of contraceptive services on-site has remained relatively stable since 2015. However, provision of implants has increased, while the number of clinics offering fertility awareness–based methods and emergency con
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Kelly, Luke. Lessons learnt from humanitarian negotiations with the Taliban, 1996-2001. Institute of Development Studies (IDS), 2021. http://dx.doi.org/10.19088/k4d.2021.11.

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This rapid literature review finds that humanitarian actors responded in a variety of ways to Taliban actions limiting principled aid in the country during the period of their rule (1996-2001). The report is focused on the findings around humanitarian negotiation and the strategy of humanitarian actors in response to Taliban policies limiting women's ability to work for humanitarian organisations or access services. The findings are not intended to imply parallels with the current situation in Afghanistan. Evidence is in the form of a number of evaluations, academic articles and lessons learne
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