An Application of a Hybrid Intelligent Algorithm for Solving Fuzzy Expected Value with Constraints
As the development of the more effective computer and the appearance of new algorithms such as neural network, genetic algorithm, lots of intelligent algorithms used to solve problems come from Fuzzy Mathematics. In probability theory and statistics, the expected value of a random variable is the integral of the random variable with respect to its probability measure, so does fuzzy variable. This paper presents an implementation technique of a hybrid intelligent algorithm for solving general fuzzy expected value within constraints. The hybrid intelligent algorithm consists of neural network and genetic algorithm.
fuzzy expected value genetic algorithm neural network triangular fuzzy variables
Renxie Shi Jianling Qi
School of Information Engineering,China University of Geosciences (Beijing),Beijing 100083, China School of Information Engineering, China University of Geosciences (Beijing), Beijing 100083, China
国际会议
哈尔滨
英文
443-446
2011-01-18（万方平台首次上网日期，不代表论文的发表时间）