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 (X i,Y i ) 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: Foster, J.A., Lutton, E., Miller, J., Ryan, C., Tettamanzi, A. (eds) Genetic Programming. EuroGP 2002. Lecture Notes in Computer Science, vol 2278. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-45984-7_30
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DOI: https://doi.org/10.1007/3-540-45984-7_30
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