权重改进粒子群算法中的自适应权重法，平衡了PSO算法的全局探索能力和局部改良能力-Weight improved particle swarm algorithm in the adaptive weighting method to balance the global exploration of the PSO algorithm is improved capacity and capacity of local

自适应的粒子群基本算法 里面没有适应度函数 可以自己编写好 然后进行调用.权重改进粒子群算法中的自适应权重法，平衡了PSO算法的全局探索能力和局部改良能力.-This is the basic matlab program of SAPSO

基于模糊自适应pso的电力系统负荷调度算法，采用的测试案例是标准1ee6g系统，约束条件包括机组出力上限限制、网络损耗和功率平衡。-Based on fuzzy adaptive pso scheduling algorithm of power system load, the test case is a standard 1 ee6g system, constraint conditions including limit the output of generating unit, t

为了平衡粒子群算法的全局搜索能力和改良局部能力，采用非线性的动态惯性权重即自适应权重法。给出一个用自适应权重的粒子群算法求多元复杂函数的最小值实例。-To balance the PSO global search capability and improved local capacity, the use of non-linear dynamic adaptive inertia weight that the weighting method. Gives an adaptive wei

自平衡PSO，自己编写的程序，之前毕设的成果，通过PSO实现路径规划，并应用到实例当中(Self balancing PSO, the program written by oneself, the result of the completion before, realizes the path planning through PSO, and applies it to the example.)