This study proposes a modified version of cultural algorithms (CAs) which benefits from rule-based system for influence function. This rule-based system selects and applies the suitable knowledge source according to the distribution of the solutions. This is important to use appropriate influence function to apply to a specific individual, regarding to its role in the search process. This rule ...

We analyze proximal methods based on entropy-like distances for the minimization of convex functions subject to nonnegativity constraints. We prove global convergence results for the methods with approximate minimization steps and an ergodic convergence result for the case of finding a zero of a maximal monotone operator. We also consider linearly constrained convex problems and establish a qua...

We compare several new SVD learning algorithms which are based on the subspace method in principal component analysis with the APEX-like algorithm proposed by Diamantaras. It is shown experimentally that the convergence of these algorithms is as fast as the convergence of the APEX-like algorithm. This paper has not been submitted elsewhere in identical or similar form, nor will it be during the...

regarding the large number of developed particle swarm optimization (pso) algorithms and the various applications for which pso has been used, selecting the most suitable variant of pso for solving a particular optimization problem is a challenge for most researchers. in this paper, using a comprehensive survey and taxonomy on different types of pso, an expert system (es) is designed to identif...