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A fuzzy system modeling algorithm for data analysis and approximate reasoning

By Kemal Kılıç, Kemal Kilic, Beth A. Sproule, I. Burhan Türksen, I. Burhan Turksen and Claudio A. Naranjo


In this paper a new fuzzy system modeling algorithm is introduced as a data analysis and approximate reasoning tool. The performance of the proposed algorithm is tested in two different data sets and compared with some well-known algorithms from the literature. In the comparison two benchmark data sets from the literature, namely the automobile mpg (miles per gallon) prediction and Box and Jenkins gas-furnace data are used. The comparisons demonstrated that the proposed algorithm can be successfully applied in system modeling

Topics: QA Mathematics
Publisher: Elsevier Science
Year: 2004
DOI identifier: 10.1016/j.robot.2004.09.005
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