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A Modified Differential Evolution Algorithm trained Pi-Sigma Neural Network for Pattern Classification

Author(s): Sibarama Panigrahi | Ashok Kumar Bhoi | Yasobanta Karali

Journal: International Journal of Soft Computing & Engineering
ISSN 2231-2307

Volume: 3;
Issue: 5;
Start page: 133;
Date: 2013;
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Keywords: Differential Evolution | Higher Order Neural Network | Pi-Sigma Network | Classification.

In this paper a modified differential evolution (DE) algorithm trained Pi-Sigma network (PSN) is used for classification. The used DE algorithm is a modification of traditional DE/rand/1/bin algorithm and novel mutation as well as crossover strategies are followed considering both exploration and exploitation. The performance of proposed methodology for pattern classification is evaluated through three well-known real world classification problems from UCI machine learning data library. The results obtained from the proposed method for classification is compared with results obtained by applying the two most popular variants of differential evolution algorithm (DE/rand/1/bin and DE/best/1/bin) and Chemical Reaction Optimization (CRO) algorithm. It is observed that the proposed method provides better classification accuracy than that of other methods.

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