{"title":"Fuzzy Petri nets","authors":"P. Cheng, K. Forward","doi":"10.1109/KES.1997.619416","DOIUrl":null,"url":null,"abstract":"Proposes a new model of a fuzzy Petri net and an algorithm to generate such a network automatically. As an example of the application of the fuzzy Petri net, it is used to classify the Iris data set. Although there are extensive examples of neural network-based classifiers in the literature, they all share the undesirable characteristic of a long learning time. We attempt to remedy this problem by using a totally different architecture, and the resulting Petri net attains comparable performance with conventional systems with just a few seconds of training.","PeriodicalId":166931,"journal":{"name":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","volume":"64 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1997-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"21","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of 1st International Conference on Conventional and Knowledge Based Intelligent Electronic Systems. KES '97","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/KES.1997.619416","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 21
Abstract
Proposes a new model of a fuzzy Petri net and an algorithm to generate such a network automatically. As an example of the application of the fuzzy Petri net, it is used to classify the Iris data set. Although there are extensive examples of neural network-based classifiers in the literature, they all share the undesirable characteristic of a long learning time. We attempt to remedy this problem by using a totally different architecture, and the resulting Petri net attains comparable performance with conventional systems with just a few seconds of training.
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