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General Information
Editor-in-chief
Prof. Wael Badawy
Department of Computing and Information Systems Umm Al Qura University, Canada
I'm happy to take on the position of editor in chief of IJCTE. We encourage authors to submit papers concerning any branch of computer theory and engineering.
IJCTE 2011 Vol.3(2): 332-337 ISSN: 1793-8201
DOI: 10.7763/IJCTE.2011.V3.328

Behaviour Analysis of Multilayer Perceptrons with Multiple Hidden Neurons and Hidden Layers

Gaurang Panchal, Amit Ganatra, Y P Kosta, and Devyani Panchal

Abstract—The terms “Neural Network” (NN) and “Artificial Neural Network” (ANN) usually refer to a Multilayer Perceptron Network. It process the records one at a time, and "learn" by comparing their prediction of the record with the known actual record. The problem of model selection is considerably important for acquiring higher levels of generalization capability in supervised learning. This paper discussed behavioral analysis of different number of hidden layers and different number of hidden neurons. It’s very difficult to select number of hidden layers and hidden neurons. There are different methods like Akaike’s Information Criterion, Inverse test method and some traditional methods are used to find Neural Network architecture. What to do while neural network is not getting train or errors are not getting reduced. To reduce Neural Network errors, what we have to do with Neural Network architecture. These types of techniques are discussed and also discussed experiment and result. To solve different problems a neural network should be trained to perform correct classification.

Index Terms—Back Propagation; Neural Network; Training; Testing; Weights.

1 gaurangpanchal.ce@ecchanga.ac.in, 2 amitganatra.ce@ecchanga.ac.in, 3 ypkosta.adm@ecchanga.ac.in, 4 devyanipanchal.it@ecchanga.ac.in

[PDF]

Cite: Gaurang Panchal, Amit Ganatra, Y P Kosta, and Devyani Panchal, "Behaviour Analysis of Multilayer Perceptrons with Multiple Hidden Neurons and Hidden Layers," International Journal of Computer Theory and Engineering vol. 3, no. 2, pp. 332-337, 2011.

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