MONTE CARLO METHODS IN FUZZY NON-LINEAR REGRESSION

被引：6
|
作者：
Abdalla, Areeg [1 ]
Buckley, James [1 ]
机构：
[1] Univ Alabama Birmingham, Math Dept, Birmingham, AL 35294 USA
来源：
NEW MATHEMATICS AND NATURAL COMPUTATION | 2008年 / 4卷 / 02期
关键词：
Fuzzy non-linear regression; Monte Carlo; random fuzzy vectors;
D O I：
10.1142/S1793005708000982
中图分类号：
O1 [数学];
学科分类号：
0701 ; 070101 ;
摘要：
We apply our new fuzzy Monte Carlo method to certain fuzzy non-linear regression problems to estimate the best solution. The best solution is a vector of triangular fuzzy numbers, for the fuzzy coefficients in the model, which minimizes an error measure. We use a quasi-random number generator to produce random sequences of these fuzzy vectors which uniformly fill the search space. We consider example problems to show that this Monte Carlo method obtains solutions comparable to those obtained by an evolutionary algorithm.
引用
收藏
页码：123 / 141
页数：19
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