Estimation of Fuzzy Regression Parameters With ANFIS and Bayesian Methods

IF 2 Q3 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Engineering reports : open access Pub Date : 2025-01-10 DOI:10.1002/eng2.13086
M. Pakdel, T. Razzaghnia, K. Fathi, A. Mostafaee
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引用次数: 0

Abstract

In fuzzy regression, estimation of centers and spreads of triangular fuzzy numbers are both performed using the same methods, such as linear programming (LP), quadratic programming (QP), fuzzy weighted linear programming (FWLP), and adaptive neuro-fuzzy inference system (ANFIS). In this article, ANFIS and Bayesian methods have been adopted to estimate centers and spreads of a triangular fuzzy numbers are applied, respectively, for estimation of centers and spreads of the triangular fuzzy data. To illustrate the efficiency of the proposed approach, three numerical examples have been used to verify the superiority of proposed method to other existing ones.

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用ANFIS和贝叶斯方法估计模糊回归参数
在模糊回归中,三角模糊数的中心和扩展的估计都使用相同的方法,如线性规划(LP)、二次规划(QP)、模糊加权线性规划(FWLP)和自适应神经模糊推理系统(ANFIS)。本文分别采用ANFIS和贝叶斯方法来估计三角模糊数的中心和扩展,用于估计三角模糊数据的中心和扩展。为了说明所提方法的有效性,用三个数值算例验证了所提方法相对于其他现有方法的优越性。
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来源期刊
CiteScore
5.10
自引率
0.00%
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0
审稿时长
19 weeks
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