In:
Advanced Materials Research, Trans Tech Publications, Ltd., Vol. 403-408 ( 2011-11), p. 3090-3094
Abstract:
In this paper, we analyze characteristics of two kinds of GA-Based neural networks. For large scale neural networks, it is necessary to optimize the initial network parameters. Using the global optimum ability of GA(Genetic Algorithm), we optimize the initial weights and biases of BPNN (Back-Propagation Neural Networks), which can avoid the local minimum. And we also optimize the spread coefficient of Gaussian Radial Basis Function of PNN (Probabilistic Neural Networks). Then the results in transformer fault diagnosis are compared. Experimental results based on Matlab show that the method of GA-Based greatly increases the reliability of diagnosis.
Type of Medium:
Online Resource
ISSN:
1662-8985
DOI:
10.4028/www.scientific.net/AMR.403-408
DOI:
10.4028/www.scientific.net/AMR.403-408.3090
Language:
Unknown
Publisher:
Trans Tech Publications, Ltd.
Publication Date:
2011
detail.hit.zdb_id:
2265002-7