A BP neural network model based on genetic algorithm for comprehensive evaluation

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

4 Citations (Scopus)

Abstract

BP algorithm can be applied in comprehensive evaluation. A hybrid neural network based on the combination of GA and BP algorithms is proposed. The algorithm made fully use of GA's global searching to improve the learning ability of BP neural network. Then, the method is used in comprehensive evaluation, which the genetic algorithm can improve the weights of the neural network and enhance the training precision of the neural network. The experimental results show that the method is valid and feasible.

Original languageEnglish
Title of host publicationProceedings - PACCS 2011
Subtitle of host publication2011 3rd Pacific-Asia Conference on Circuits, Communications and System
DOIs
Publication statusPublished - 2011
Event2011 3rd Pacific-Asia Conference on Circuits, Communications and System, PACCS 2011 - Wuhan, China
Duration: 17 Jul 201118 Jul 2011

Publication series

NameProceedings - PACCS 2011: 2011 3rd Pacific-Asia Conference on Circuits, Communications and System

Conference

Conference2011 3rd Pacific-Asia Conference on Circuits, Communications and System, PACCS 2011
Country/TerritoryChina
CityWuhan
Period17/07/1118/07/11

Keywords

  • ANN
  • Comprehensive Evaluation
  • Genetic algorithm

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