شماره ركورد كنفرانس :
4418
عنوان مقاله :
A Stochastic Gradient-Directed Particle Swarm Optimization
پديدآورندگان :
Khodambashi Siavash Electrical and Computer Engineering Department, Shahid Beheshti University;G.C, Tehran , Iran , Zakerolhosseini Ali Electrical and Computer Engineering Department, Shahid Beheshti University;G.C, Tehran , Iran
كليدواژه :
Particle swarm optimization (PSO) , gradient , global optimization problem
عنوان كنفرانس :
يازدهمين كنفرانس سراسري سيستم هاي هوشمند
چكيده فارسي :
Particle swarm optimization algorithms have been widely used for optimization problems. These kinds of algorithms are popular due to their simplicity and good efficiency. In this paper we propose a novel algorithm based on conventional PSO with some modifications which outperforms previous methods and presents more accurate results. Our proposed method uses gradient coefficient for exactness and normal distribution for diversity in exploration. We examined the performance of our method with several well-known mathematical functions
