@article{37afb2a732a94d13bea5f28a15246acc,
title = "A review on applications of genetic algorithm for artificial neural network",
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",
author = "{Ali Saud Al Tobi}, Maamer and Geraint Bevan and Peter Wallace and David Harrison and Ramachandran, {K. P.}",
note = "Acceptance confirmation in SAN No DOI available AAM: contacted publisher 8-3-17 and 14-8-17, made open VoR version available to download Exception rc'd 8-9-17 (email in SAN) ^Exception status: author email in SAN; agreed no exception can be applied (library exception review, October 2018) ",
year = "2016",
month = sep,
day = "30",
language = "English",
volume = "4",
pages = "50--54",
journal = "International Journal of Advance Computational Engineering and Networking",
issn = "2320-2106",
publisher = "Institute of Technology and Research",
number = "9",
}