简述粒子群算法的原理及改进

本文主要介绍了粒子群(Praticle Swarm Optimizer,PSO)算法,它是一种新的基于群体智能的优化算法,是在鸟群觅食行为规律的基础上提出的。他其结构简单、参数调整简单易行,更适合计算机编程处理,但在该算法中,如果粒子速度始终保持较大,容易"飞越"解空间中的最优区域,造成发散现象,收敛不到最优解,如果从惯性权重的自适应方面来调整,就可以很好的解决该问题。

PSO Algorithm and the Principle of Improving

This text mainly introduced a grain sons(the Optimizer of the Praticle Swarm, PSO) calculate way,it is a kind of new according to community intelligence of excellent turn calculate way,is the foundation which looks for food behavior regulation in the birds up put forward. He its structure is simple,the parameter adjust to go in brief and easily,the more in keeping with calculator weaves a distance a processing,but in that calculate way, if the grain sub-speed keeps always more and greatly,the superior district in the easy "fly more" solution space,result in to dissipate of phenomenon,could not refrain from rash action the superior solution,if heavy from the inertial power of adjust from the orientation aspect,it can be good to resolve that problem.