NDLI: Bacterial Foraging Optimization Algorithm for neural network learning enhancement

Content Provider	IEEE Xplore Digital Library
Author	AL-Hadi, I.A.A. Hashim, S.Z.M. Shamsuddin, S.M.H.
Copyright Year	2011
Description	Author affiliation: Soft Computing Research Group, Faculty of Computer Science and Information Systems, Universiti Teknology Malaysia, Skudai, 81300 Johor, Malaysia (AL-Hadi, I.A.A.; Hashim, S.Z.M.; Shamsuddin, S.M.H.)
Abstract	Backpropagation algorithm is widely used to solve many real-world problems, using the concept of Multilayer Perceptron. However, main disadvantages of Backpropagation are the convergence rate of it being relatively slow, and it is often trapped in the local minima. To solve this problem, it is found in the literatures, an evolutionary algorithm such as Particle Swarm Optimization algorithm is applied in feedforward neural network to optimize the learning process in terms of convergence rate and classification accuracy but this process needs longer training time. Hence to provide an alternative solution this study introduced, Bacterial Foraging Optimization Algorithm to be utilized in feedforward neural network to enhance the learning process and improve its convergence rate and classification accuracy. The developed Bacterial Foraging Optimization Algorithm Feedforward Neural Network (BFOANN) is compared against Particle Swarm Optimization Feedforward Neural Network (PSONN). The results show that BFOANN outperforms PSONN with better convergence rate and classification accuracy.
Starting Page	200
Ending Page	205
File Size	549321
Page Count	6
File Format	PDF
ISBN	9781457721519
e-ISBN	9781457721526
DOI	10.1109/HIS.2011.6122105
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-05
Publisher Place	Malaysia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Training Backpropagation Microorganisms Neural Network Artificial neural networks Bacterial Foraging Classification algorithms Optimization Particle Swarm Convergence Cancer
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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