{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2022,3,28]],"date-time":"2022-03-28T21:48:31Z","timestamp":1648504111491},"reference-count":16,"publisher":"Cambridge University Press (CUP)","issue":"4","license":[{"start":{"date-parts":[[2003,11,1]],"date-time":"2003-11-01T00:00:00Z","timestamp":1067644800000},"content-version":"unspecified","delay-in-days":0,"URL":"https:\/\/www.cambridge.org\/core\/terms"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["AIEDAM"],"published-print":{"date-parts":[[2003,11]]},"abstract":"<jats:p>We present a methodology of learning fuzzy rules using an iterative \ngenetic algorithm (GA). The approach incorporates a scheme of \npartitioning the entire solution space into individual subspaces. It \nthen employs a mechanism to progressively relax or tighten the \nconstraint. The relaxation or tightening of constraint guides the GA to \nthe subspace for further iteration. The system referred to as the \niterative GA learning module is useful for learning an efficient fuzzy \ncontrol algorithm based on a predefined linguistic terms set. The \noverall approach was applied to learn a fuzzy algorithm for a water \nbath temperature control. The simulation results demonstrate the \neffectiveness of the approach in automating an industrial process.<\/jats:p>","DOI":"10.1017\/s0890060403174057","type":"journal-article","created":{"date-parts":[[2008,4,21]],"date-time":"2008-04-21T06:30:38Z","timestamp":1208759438000},"page":"335-347","source":"Crossref","is-referenced-by-count":6,"title":["Iterative genetic algorithm for learning efficient fuzzy rule set"],"prefix":"10.1017","volume":"17","author":[{"given":"MENG HIOT","family":"LIM","sequence":"first","affiliation":[]},{"given":"WILLIE","family":"NG","sequence":"additional","affiliation":[]}],"member":"56","published-online":{"date-parts":[[2003,11,1]]},"reference":[{"key":"S0890060403174057_ref015","doi-asserted-by":"publisher","DOI":"10.1109\/41.170970"},{"key":"S0890060403174057_ref014","unstructured":"Ng, W.L. & Lim, M.H. (2002).Genetic optimisation of fuzzy rule set for industrial plantautomation.Fourth Asia\u2013Pacific Conf. 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(1989).Genetic Algorithms in Search, Optimisation and Machine Learning,pp.76\u201379.New York:Addison\u2013Wesley."},{"key":"S0890060403174057_ref011","unstructured":"Lin, C.T. , Juang, C.F. , & Li, C.P. (1999).Temperature control with a neural fuzzy inference network.IEEE Transactions on Systems, Man, and Cybernetics, 29,440\u2013451."},{"key":"S0890060403174057_ref010","doi-asserted-by":"publisher","DOI":"10.1023\/A:1008743718053"},{"key":"S0890060403174057_ref002","unstructured":"Goldberg, D.E. & Lingle, R. (1985).Alleles, loci and the travelling salesman problem.Proc. First Int. Conf. Genetic Algorithms and Their Applications, pp.154\u2013158."},{"key":"S0890060403174057_ref016","unstructured":"Thrift, P. (1991).Fuzzy logic synthesis with genetic algorithms.Proc. Fourth Int. Conf. Genetic Algorithms, pp.509\u2013513."},{"key":"S0890060403174057_ref005","doi-asserted-by":"publisher","DOI":"10.1109\/91.388168"},{"key":"S0890060403174057_ref006","doi-asserted-by":"publisher","DOI":"10.1109\/3477.836377"},{"key":"S0890060403174057_ref007","unstructured":"Karr, C.L. (1991).Design of an adaptive fuzzy logic controller using a geneticalgorithm.Proc. Fourth Int. Conf. Genetic Algorithms, pp.450\u2013457."}],"container-title":["Artificial Intelligence for Engineering Design, Analysis and Manufacturing"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.cambridge.org\/core\/services\/aop-cambridge-core\/content\/view\/S0890060403174057","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2019,5,6]],"date-time":"2019-05-06T18:19:14Z","timestamp":1557166754000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.cambridge.org\/core\/product\/identifier\/S0890060403174057\/type\/journal_article"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003,11]]},"references-count":16,"journal-issue":{"issue":"4","published-print":{"date-parts":[[2003,11]]}},"alternative-id":["S0890060403174057"],"URL":"https:\/\/doi.org\/10.1017\/s0890060403174057","relation":{},"ISSN":["0890-0604","1469-1760"],"issn-type":[{"value":"0890-0604","type":"print"},{"value":"1469-1760","type":"electronic"}],"subject":[],"published":{"date-parts":[[2003,11]]}}}