A review on applications of genetic algorithm for artificial neural network

Maamer Ali Saud Al Tobi, Geraint Bevan, Peter Wallace, David Harrison, K. P. Ramachandran

Research output: Contribution to journalArticlepeer-review

233 Downloads (Pure)


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.
Original languageEnglish
Pages (from-to)50-54
Number of pages5
JournalInternational Journal of Advance Computational Engineering and Networking
Issue number9
Publication statusPublished - 30 Sept 2016


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


Dive into the research topics of 'A review on applications of genetic algorithm for artificial neural network'. Together they form a unique fingerprint.

Cite this