نتایج جستجو برای: modified pso
تعداد نتایج: 260689 فیلتر نتایج به سال:
Original scientific paper Particle swarm optimization (PSO) based optimization algorithms are simple and easily implementable techniques with low computational complexity, which makes them good tools for solving large-scale nonlinear optimization problems. This paper presents a modified version of the original method by combining PSO with a local search technique at the end of each iteration cy...
Online handwriting recognition today has special interest due to increased usage of the hand held devices and it has become a difficult problem because of the high variability and ambiguity in the character shapes written by individuals. One major problem encountered by researchers in developing character recognition system is selection of efficient features (optimal features). In this paper, P...
Developing a mathematical model has become an inevitable need in studies of all disciplines. With advancements technology, there is emerging to develop complex models. System identification popular way constructing models highly processes when analytical not feasible. One the many architectures system utilize Local Model Network (LMN). Hierarchical Tree (HILOMOT) iterative LMN training algorith...
This paper introduces a modified Particle Swarm . Optimizer which deals with permutation problems. Particles are defined as permutations of a group of unique values. Velocity updates are redefined based on the similarity of two particles. Particles change their permutations with a random rate defined by their velocities. A mutation factor is introduced to prevent the current pBest from becoming...
This paper presents a hybrid filter–wrapper feature subset selection algorithm based on particle swarm optimization (PSO) for support vector machine (SVM) classification. The filter model is based on the mutual information and is a composite measure of feature relevance and redundancy with respect to the feature subset selected. The wrapper model is a modified discrete PSO algorithm. This hybri...
In this paper a modified Particle Swarm Optimization (PSO) algorithm called Autonomous Groups Particles Swarm Optimization (AGPSO) is proposed to further alleviate the two problems of trapping in local minima and slow convergence rate in solving high dimensional problems. The main idea of AGPSO algorithm is inspired by individuals’ diversity in bird flocking or insect swarming. In natural colon...
Clustering is a process for partitioning datasets. This technique is a challenging field of research in which their potential applications pose their own special requirements. K-Means is the most extensively used algorithm to find a partition that minimizes Mean Square Error (MSE) is an exigent task. The Object Function of the K-Means is not convex and hence it may contain local minima. ACO met...
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