A review on applications of genetic algorithm for artificial neural network

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  • Saud Al Tobi, M.A. et al (2016) A review on applications of genetic algorithm in artificial intelligence neural network

    Rights statement: This is the author accepted manuscript of the article: Al Tobi, M. A. S., Bevan, G., Wallace, P., Harrison, D., & Ramachandran, K. P. (2016). A review on applications of genetic algorithm for artificial neural network. International Journal of Advanced Computational Engineering and Networking, 4 (9), 50-54. Copyright © 2016 International Journal of Advance Computational Engineering and Networking (IJACEN).

    Accepted author manuscript, 946 KB, PDF-document

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Original languageEnglish
Pages (from-to)50-54
Number of pages5
JournalInternational Journal of Advanced Computational Engineering and Networking
Volume4
Issue number9
StatePublished - 30 Sep 2016

Abstract

Artificial neural networks (ANN) can be used as automatic classifiers of faults in machines, reducing errors due to human misinterpretation. Multilayer Perceptron neural networks (MLP) are a popular type of ANN due totheir simplicity and efficiency. Genetic Algorithms (GA) can be combined with MLP-ANN to optimize the classification through selection and training. This paper reviews and discusses the applications of GA with ANN and the future scope of applying GA for the training of ANN based machinery fault diagnosis in order to fill the gaps of traditional Back Propagation algorithm (BP). Keywords- Artificial Neural Network, Genetic Algorithm, Multilayer Perceptron, Back Propagation, Training Algorithm.

Keywords

  • artificial neural network, genetic algorithm, multilayer perceptron, back propagation, training algorithm

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