Title: Fusion of clonal selection algorithm and harmony search method in optimisation of fuzzy classification systems

Authors: Xiaolei Wang, Xiao-Zhi Gao, Seppo J. Ovaska

Addresses: Department of Electrical Engineering, Helsinki University of Technology, Otakaari 5 A, FI-02150 Espoo, Finland. ' Department of Electrical Engineering, Helsinki University of Technology, Otakaari 5 A, FI-02150 Espoo, Finland. ' Department of Electrical Engineering, Helsinki University of Technology, Otakaari 5 A, FI-02150 Espoo, Finland

Abstract: This paper presents a hybrid optimisation method based on the fusion of the clonal selection algorithm (CSA) and harmony search (HS) technique. The CSA is employed to improve the harmony memory members in the HS method. The hybrid optimisation algorithm is further used to optimise Sugeno fuzzy classification systems for the Fisher Iris data and wine data classification. Computer simulations results demonstrate the remarkable effectiveness of our new approach.

Keywords: clonal selection algorithm; CSA; harmony search method; HS method; hybrid optimisation methods; fuzzy classification systems; simulation; bio-inspired computation.

DOI: 10.1504/IJBIC.2009.022776

International Journal of Bio-Inspired Computation, 2009 Vol.1 No.1/2, pp.80 - 88

Published online: 26 Jan 2009 *

Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article