个体决策认知与社会系数的粒子群算法及应用

作为重要的参数,粒子群算法的认知系数与社会系数的选择策略要么始终把这两个系数设置为一个固定的数,要么在相同的代对所有粒子采用相同的参数设置.每个粒子有不同的生活经验,每个粒子会做出不同的个体决策,因此这两个参数应该不同.通过个体决策的机制和方法,文章通过一种新的适应值判别方法——适应值变化率来动态调整认知系数与社会系数.把改进的粒子群算法应用到非线性方程组求解问题中,仿真结果表明它具有较大的优势.

Application of Particle Swarm Optimization with Individual Decision Cognitive and Social Coefficient

As an important parameter, cognitive coefficient and social coefficient are always set a fixed number or set the.same at the same genetion in Particle swam optimization （PSO）. Since each particle maintains different living experience, thus different individual will make a dif- ferent decision, and therefore the two parameters should have some difference. With the assistant of mature individual decision way and mechanism, this paper dynamically adjusts cognitive coeffi- cient by the change ratio of fitness value. The improved PSO is applied into solving nonlinear e- quations problem, simulation results show more superior.