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The Model of Power Plant Selection Based on Improved Fuzzy Neural Network

The paper adopts rough set reduction algorithm to reduce the influence factors of power plant selection and eliminate the uncorrelated attribution, through which we can obtain typical samples. After this, adopting fuzzy method to calculate the membership degree of the typical samples, which are looked on as the input of BP Neural Network and the expert values are as the expected output to train the network. Through this way the training speed and accuracy will be improved. In this way, we will obtain the network output namely the evaluation result of the case when we calculate using the trained network. According to the result, we can evaluate and make a decision for power plant selection.