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General Information
Editor-in-chief

Prof. Pascal Lorenz
University of Haute Alsace, France
 
It is my honor to be the editor-in-chief of IJFCC. The journal publishes good papers in the field of future computer and communication. Hopefully, IJFCC will become a recognized journal among the readers in the filed of future computer and communication.

IJFCC 2013 Vol.2(6): 567-569 ISSN: 2010-3751
DOI: 10.7763/IJFCC.2013.V2.228

The Impact of Training Iterations on ANN Applications Using BPNN Algorithm

Qamar Abbas, Waqas Haider Bangyal, and Jamil Ahmad
Abstract—Training Artificial Neural Network (ANN) has attracted many researchers for a long time. This paper investigates the impact of training iterations of ANN using Backpropagation Neural Network (BPNN) algorithm. The two sets of adjustable parameters, i.e., the learning rate and number of hidden nodes in the hidden layer are used to analyze the impact of training iterations of ANN applications is used. The applications that are used in this research are XOR problem and Digit Recognition. The efficacy of the results using BPNN algorithm is shown through an analysis of the impact of training iterations and by presenting simulation results from two different applications.

Index Terms—XOR, digit, training iterations, BPNN

The authors are with Iraq University, Islamabad, Pakistan (e-mail: qamar.bhk@gmail.com, waqas_bangyal@hotmail.com, jamil.ahmad@abasyn.edu.pk).

[PDF]

Cite:Qamar Abbas, Waqas Haider Bangyal, and Jamil Ahmad, "The Impact of Training Iterations on ANN Applications Using BPNN Algorithm," International Journal of Future Computer and Communication vol. 2, no. 6, pp. 567-569, 2013.

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