A Systematic Approach to OptimizinghValue for Fuzzy Linear Regression with Symmetric Triangular Fuzzy Numbers
A Systematic Approach to OptimizinghValue for Fuzzy Linear Regression with Symmetric Triangular Fuzzy Numbers
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DOI：
10.1155/2013/210164
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发表时间：
2013-12
影响因子：
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通讯作者：
Xilong Liu;Yizeng Chen
中科院分区：
文献类型：
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作者：
Xilong Liu;Yizeng Chen
提出了一种基于对称三角模糊数最小模糊度准则的模糊线性回归（FLR）优化方法。首先，定义了一个新的可信度概念，用来评价给定样本数据对时不同取值的FLR模型的性能。其次，在定义可信度概念的基础上，建立了可信度优化的规划模型。最后，数值研究和真实的应用都表明，本文提出的方法是有效的，即对于给定的样本数据对，可以确定最优值。
A systematic approach is proposed to optimize value for fuzzy linear regression (FLR) analysis using minimum fuzziness criteria with symmetric triangular fuzzy numbers (TFNs). Firstly, a new concept of credibility is defined to evaluate the performance of FLR models with different values when a set of sample data pairs is given. Secondly, based on the defined concept of credibility, a programming model is formulated to optimize the value of . Finally, both the numerical study and the real application show that the approach proposed in this paper is effective and efficient; that is, optimal value for can be determined definitely with respect to a set of given sample data pairs.