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APPLICATION OF GRADIENT DESCENT AND GENETIC ALGORITHMS TO THE TRAPEZOIDAL FUZZY SET BASED APPROXIMATE SAM

Le Ngoc Thanh 1
Volume & Issue: Vol. 9 No. 9 (2006) | Page No.: 37-48 | DOI: 10.32508/stdj.v9i9.3062
Published: 2006-09-30

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Copyright The Author(s) 2023. This article is published with open access by Vietnam National University, Ho Chi Minh city, Vietnam. This article is distributed under the terms of the Creative Commons Attribution License (CC-BY 4.0) which permits any use, distribution, and reproduction in any medium, provided the original author(s) and the source are credited. 

Abstract

Parameter learning and Optimal learning, as well to all other knowledge presentative models, have an essential sense to the quality and effectivity in approximation of SAM. This paper presents not only an applied research on gradient descent algorithm and genetic algorithm to the parameter learning process and the optimal learning process of trapezoidal fuzzy set based SAM system, but also, an application of the research to the time-series prediction.

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