Thinking capability of saplings growing up algorithm

Authors:
Ali Karci;Bilal Alatas
Affiliations:
Department of Computer Engineering, Firat University, Elazig, Turkey;Department of Computer Engineering, Firat University, Elazig, Turkey
Venue:
IDEAL'06 Proceedings of the 7th international conference on Intelligent Data Engineering and Automated Learning
Year:
2006

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Abstract

Saplings Growing up Algorithm (SGA) is a novel computational intelligence method inspired by sowing and growing up of saplings. This method contains two phases: Sowing Phase and Growing up Phase. Uniformed sowing sampling is aim to scatter evenly in the feasible solution space. Growing up phase contains three operators: mating, branching, and vaccinating operator. In this study thinking capability of SGA has been defined and it has been demonstrated that sapling population generated initially has diversity. The similarity of population concludes the interaction of saplings and at consequent, they will be similar. Furthermore, the operators used in the algorithm uses similarity and hence the population has the convergence property.