A Multi-strategy Differential Evolution Algorithm for Financial Prediction with Single Multiplicative Neuron

Authors:
Chukiat Worasucheep;Prabhas Chongstitvatana
Affiliations:
Applied Computer Science, Department of Mathematics, Faculty of Science, King Mongkut's University of Technology Thonburi, Bangkok, Thailand 10140;Department of Computer Engineering, Faculty of Engineering, Chulalongkorn University, Bangkok, Thailand 10330
Venue:
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Year:
2009

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Abstract

This paper proposes a differential evolution (DE) algorithm that combines the strengths of multiple strategies together. The selection of strategy and control parameters for each individual happens every learning period. Thus the user gains the benefits of different strategies without difficult fine tuning of control parameters. The performance of the proposed MDE algorithm is evaluated on well-known benchmark functions and is superior to some other efficient and widely used variants of DE. In addition, MDE is applied to optimize both weights and biases of a single multiplicative neuron for prediction of DJIA with 3228 samples. Experiments show its better performance than other methods in learning ability and generalization.