JCOM_V1_N3_RP1
A New Adaptive BFO Based on PSO for Learning Neural Network
Ahmed Alostaz
Mohammed Alhanjouri
Journal on Computer Science
2347–6141
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3
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16
Learning Neural Network, BFO, PSO, Adaptive BFO
In this paper, we introduce a new learning algorithm for neural network. A New Adaptive bacteria foraging optimization based on particle swarm optimization(ABFO_PSO) is used in learning neural network. This paper reviews Feed Forward Neural Network (FFANN), and the drawback of back- propagation learning method. Particle Swarm Optimization (PSO) is also described. Moreover, using the PSO in learning neural network is reviewed. Bacterial Foraging Optimization (BFO) is a novel heuristic algorithm inspired from forging behavior of E. coli. It is predominately used to find solutions for real-world problems, but it has problem with time and convergence behaviour. To introduce ABFO_PSO, that provide solution for BFO problem, we make a hybrid between PSO and BFO. Moreover, BFO and ABFO_PSO are applied for learning neural network. The comparison between the results of ABFO_PSO, BFO and PSO for learning neural network shows the strength of new method.
September - November 2013
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