搜索资源列表
RandWPSO
- 随机权重粒子群算法，来自来自于《精通MATLAB最优化计算》- pso with random weight
RandWPSO
- 权重改进粒子群算法中的随机权重法，将标准PSO算法中设定w为服从某种随机分布的随机数，这样一定程度上可从两方面克服w的线性递减所带来的不足-Weights improved particle swarm algorithm in the random weight method, the standard PSO algorithm to set w to obey a random distribution of the random numbers, so to a certain exte
RandWPSO
- 随机粒子群算法，简单高效。非常不错的一个优化算法程序-Stochastic particle swarm algorithm, simple and efficient. An optimization algorithm is very good program
RandPSO
- 随机权重的粒子群算法，优化过程中权重随机变化-RandWPSO
RandWPSO_LinWPSO_LnCPSO
- 用MATLAB实现RandWPSO、LinWPSO、LnCPSO算法，程序没错误，可以直接运行，非常适合刚学PSO者-Implementation of RandWPSO, LinWPSO, LnCPSO algorithm with MATLAB, the program no error, can be directly run, very suitable for just learning PSO
RandWPSO
- 随机权重粒子群优化算法，将w用w_min和w_max制约取值，避免局部最优解。-Random weight particle swarm optimization algorithm, the W with w_min and w_max control value, avoid the local optimal solution.
RandWPSO
- 对粒子群算法的改进，利用一类名为随机权重法来更新粒子的速度和位置，用来解决静态单目标优化问题-It is the improved particle swarm optimization algorithm. It introduced a kind method named random weight to update the position and velocity of the particle. It can be used for handle single objective p
RandWPSO
- 用随机权重粒子群优化算法求解无约束优化问题-Heavy Particle Swarm Optimization with Random Weight unconstrained optimization problems
PSOs
- 13种粒子群优化算法 PSO,AsyLnCPSO,BreedPSO,CLSPSO,LinWPSO,LnCPSO,RandWPSO,SAPSO,SecPSO,SecVibratPSO,SelPSO,SimuAPSO,YSPSO-13 kind of particle swarm optimization algorithm
RandWPSO
- 随机权重粒子群算法，解决无约束问题，入门级别。粒子群算法结构简单，易于实现，非常经典。(random weight particle swarm optimization for unconstrained problems)
13种PSO算法以及课件
- 各算法对应的问题如下： PSO 用基本粒子群算法求解无约束优化问题 YSPSO 用带压缩因子的粒子群算法求解无约束优化问题 LinWPSO 用线性递减权重粒子群优化算法求解无约束优化问题 SAPSO 用自适应权重粒子群优化算法求解无约束优化问题 RandWPSO 用随机权重粒子群优化算法求解无约束优化问题 LnCPSO 用学习因子同步变化的粒子群优化算法求解无约束优化问题 AsyLnCPSO 用学习因子异步变化的粒子群优化算法求解无约束优化问题
经典即变异粒子群优化算法
- AsyLnCPSO算法，BreedPSO算法，CLSPSO算法，经典粒子群PSO算法，RandWPSO算法等等经典粒子群变异算法模型(AsyLnCPSO algorithm, BreedPSO algorithm, CLSPSO algorithm, classical particle swarm optimization PSO algorithm, RandWPSO algorithm and so on, and so on.)