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Bacterial type algorithms used for fuzzy rule base extraction

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PL
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PL
The paper gives an overview of various bacterial type evolutionary algorithms used for fuzzy rule based identification. In order to find an optimal rule base from the input-output training data set, several improved algorithms have been developed in recent years. The task is to increase the models’ accuracy and convergence speeds by modifying a part of the Mamdani-type inference system.
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online
2015-04-21
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bwmeta1.element.ojs-nameId-6e3e8ea9-5a94-37a7-828b-e6cd5da23db6-year-2015-article-1741
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