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New results on fuzzy regression by using genetic programming

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (2002) 2278 308-315
DOI: 10.1007/3-540-45984-7_30
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Abstract

In this paper we continue the work on symbolic fuzzy regression problems. That means that we are interested in finding a fuzzy function f, which best matches given data pairs (Xi, Yi) 1 ≤ i ≤ k of fuzzy numbers. We use a genetic programming approach for finding a suitable fuzzy function and will present test results about linear, quadratic and cubic fuzzy functions.

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Golubski, W. (2002). New results on fuzzy regression by using genetic programming. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 2278, pp. 308–315). Springer Verlag. https://doi.org/10.1007/3-540-45984-7_30

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