Abstract
This paper presents the fuzzy regression approach to the automotive industry optimization problem. The flywheel assembly process is subject to investigation, as its parameters require optimization. The paper contains: problem definition, presentation of the measured data and the final analysis with two alternative approaches: the fuzzy regression and the classical regression. The benefits of the fuzzy regression approach are shown in the case of small size samples.
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Pietraszek, J. (2012). Fuzzy Regression Compared to Classical Experimental Design in the Case of Flywheel Assembly. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Artificial Intelligence and Soft Computing. ICAISC 2012. Lecture Notes in Computer Science(), vol 7267. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29347-4_36
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DOI: https://doi.org/10.1007/978-3-642-29347-4_36
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-29346-7
Online ISBN: 978-3-642-29347-4
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