ANN Approach for Error Optimization in Process Synchronization Using Back-Propagation Algorithm

Authors(2) :-Sayma Bano, Neelendra Badal

The work includes in this paper is inspired from the convolution involved for solving the problems by a neural network. The aspiration of this paper is to demonstrate the minimization of error for problem-solving techniques, like process synchronization, Classification etc. The work includes three Artificial Neural Network Algorithms i.e., Feed-forward, Back-propagation and Output-Hidden Weight Optimization. Optimization is being achieved with the minimized error rate for the problem-solving using neural system approach.

Authors and Affiliations

Sayma Bano
Department of Computer Science & Engineering, Kamla Nehru Institute of Technology, Sultanpur, Uttar Pradesh, India
Neelendra Badal
Department of Computer Science & Engineering, Kamla Nehru Institute of Technology, Sultanpur, Uttar Pradesh, India

Back-propagation Error Methodology, Optimization, Synchronization

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Publication Details

Published in : Volume 3 | Issue 5 | May-June 2018
Date of Publication : 2018-06-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 477-485
Manuscript Number : CSEIT183594
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Sayma Bano, Neelendra Badal , "ANN Approach for Error Optimization in Process Synchronization Using Back-Propagation Algorithm", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 3, Issue 5, pp.477-485, May-June-2018. |          | BibTeX | RIS | CSV

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