1) linear descend inertia weight
线性递减惯性权重
1.
The particle swarm optimization algorithm with constriction factor and linear descend inertia weight,namely W-K-PSO is applied to the intelligent schedule of vehicles oper.
采用兼顾公交公司与乘客双方利益的公交车辆调度模型,将带收缩因子和线性递减惯性权重的粒子群优化算法(W-K-PSO)应用到公交智能排班中。
2) linearly decreasing weight
线性递减权
1.
New algorithm chooses the suitable inertia weight for every swarm through the linearly decreasing weight policy, and uses the immune evolutionary principle to improve the process of PSO.
算法采用线性递减权策略为各个粒子选取适当惯性权值,利用免疫进化思想改进粒子群优化过程,同时利用聚类经验规则k≤n确定聚类数k的初始搜索范围,以性能代价函数为依据在聚类数目未知的情况下实现动态聚类。
3) inertia weight
惯性权重
1.
Research advances on inertia weight in particle swarm optimization;
粒子群优化算法中惯性权重的研究进展
2.
Modified particle swarm optimizer using non-linear inertia weight;
一种非线性改变惯性权重的粒子群算法
3.
Particle swarm optimization with self-adaptive stochastic inertia weight;
具有自适应随机惯性权重的PSO算法
4) linear decreasing
线性递减
1.
Because of this,a particle swarm optimization algorithm with the strategy of nonlinear decreasing inertia weight is proposed based on the standard particle swarm algorithm.
结果提出一种非线性递减惯性权重策略的粒子群优化算法。
5) Linearly decreasing inertia weight
惯性权重线性下降
6) Nonl
非线性惯性权重微粒群
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