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231223s1999 xx |||||o 00| ||eng c |
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|a 10.1109/3477.775268
|2 doi
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|a eng
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|a Thawonmas, R
|e verfasserin
|4 aut
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|a Function approximation based on fuzzy rules extracted from partitioned numerical data
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|c 1999
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|a Text
|b txt
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|a ƒaComputermedien
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|a ƒa Online-Ressource
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| 500 |
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|a Date Completed 02.10.2012
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|a Date Revised 06.02.2008
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|a published: Print
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|a Citation Status PubMed-not-MEDLINE
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|a We present an efficient method for extracting fuzzy rules directly from numerical input-output data for function approximation problems. First, we convert a given function approximation problem into a pattern classification problem. This is done by dividing the universe of discourse of the output variable into multiple intervals, each regarded as a class, and then by assigning a class to each of the training data according to the desired value of the output variable. Next, we partition the data of each class in the input space to achieve a higher accuracy in approximation of class regions. Partition terminates according to a given criterion to prevent excessive partition. For class region approximation, we discuss two different types of representations using hyperboxes and ellipsoidal regions, respectively. Based on a selected representation, we then extract fuzzy rules from the approximated class regions. For a given input datum, we convert, or in other words, defuzzify, the resulting vector of the class membership degrees into a single real value. This value represents the final result approximated by the method. We test the presented method on a synthetic nonlinear function approximation problem and a real-world problem in an application to a water purification plant. We also compare the presented method with a method based on neural networks
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|a Journal Article
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|a Abe, S
|e verfasserin
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|i Enthalten in
|t IEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society
|d 1996
|g 29(1999), 4 vom: 01., Seite 525-34
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|g volume:29
|g year:1999
|g number:4
|g day:01
|g pages:525-34
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|u http://dx.doi.org/10.1109/3477.775268
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