Multispecies Coevolution Particle Swarm Optimization Based on Previous Search History
نویسندگان
چکیده
منابع مشابه
S3PSO: Students’ Performance Prediction Based on Particle Swarm Optimization
Nowadays, new methods are required to take advantage of the rich and extensive gold mine of data given the vast content of data particularly created by educational systems. Data mining algorithms have been used in educational systems especially e-learning systems due to the broad usage of these systems. Providing a model to predict final student results in educational course is a reason for usi...
متن کاملSearch Optimization using Multiobjective Particle Swarm Optimization
The reusability provides many benefits such as increasing productivity, Reliability & Quality along with reducing the cost &development time and if the number of components developed is not according to the requirement then the technique of reusability is of great help. The main problem faced by the CBSE in reusability is to select the component for reuse as before reusing there is need to retr...
متن کاملDiversity Guided Particle Swarm Optimization algorithm based on Search Space Awareness Particle Dispersion (DGPSO)
Diversity control in the particle swarm optimization (PSO) algorithm is one of the important issues that influence the process of finding global optimal solution. In this study we create a historical process to find best area of the search space for population dispersion guide on PSO algorithm, and name Diversity Guided Particle Swarm Optimization algorithm (DGPSO) algorithm. Hence we propose a...
متن کاملA Modified Particle Swarm Optimization on Search Tasking
Recently, more and more researches have been conducted on the multi-robot system by applying bioinspired algorithms. Particle Swarm Optimization (PSO) is one of the optimization algorithms that model a set of solutions as a swarm of particles that spread in the search space. This algorithm has solved many optimization problems, but has a defect when it is applied on search tasking. As the time ...
متن کاملStudy on the Local Search Ability of Particle Swarm Optimization
Particle swarm optimization (PSO) has been shown to perform well on many optimization problems. However, the PSO algorithm often can not find the global optimum, even for unimodal functions. It is necessary to study the local search ability of PSO. The interval compression method and the probabilistic characteristic of the searching interval of particles are used to analyze the local search abi...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: Discrete Dynamics in Nature and Society
سال: 2017
ISSN: 1026-0226,1607-887X
DOI: 10.1155/2017/5193013