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. © Springer-Verlag Berlin Heidelberg 2006.
CITATION STYLE
Karci, A., & Alatas, B. (2006). Thinking capability of saplings growing up algorithm. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 4224 LNCS, pp. 386–393). Springer Verlag. https://doi.org/10.1007/11875581_47
Mendeley helps you to discover research relevant for your work.