Grammatical Differential Evolution Adaptable Particle Swarm Optimizer for Artificial Neural Network Training

Tapas Si

In this paper, Grammatical Differential Evolution (GDE) Adaptable Particle Swarm Optimizer (GDE-APSO) is applied in training of Feed –Forward Neural Network (FNN). The error function of FNN is a highly multimodal function having too many local optima. GDE-APSO algorithm can solve multimodal function efficiently and effectively. The devised method is termed as GDE-APSO-NN and it is used to train FNN for XOR problem. Here, the CLPSO and DE/best/1/bin algorithms are also applied to train FNN for the same problem to make a comparative study. The experimental study shows that GDE-APSO performed better than CLPSO and DE/best/1/bin algorithm in FNN training.

Select Volume / Issues:

• Volume 4 Issue 1, Jan. 2013

Year:

2013

Type of Publication:

Article

Keywords:

Grammatical Differential Evolution; Particle Swarm Optimization; CLPSO; Artificial Neural Network

Journal:

IJECCE

Volume:

4

Number:

1

Pages:

239-243

Month:

January