基于禁忌搜索的自适应粒子群算法 关键词：粒子群；惯性权重；禁忌搜索 [gap=1084]Key words：particle swarm optimization；inertia weight；tabu search
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...惯性权重；数学模型 [gap=965]rds: particle swarm algorithm;economic operation;optimizing operation principle;self-adapting inertia;the mathematical model ..
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已有学者采用PSO算法的线性递减 惯性权重（LinearlyDecreasing inertia Weight，LDW）的策略乜¨， 所设计的滤波器性能优良。
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Twice Gaussian mutation controlled the algorithm process. Inertia weight was adjusted dynamically.
该算法通过两次高斯变异控制算法进程,同时动态调节惯性权重。
参考来源 - 基于双变异算子的混合粒子群优化算法·2,447,543篇论文数据，部分数据来源于NoteExpress
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。
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.
该算法通过两次高斯变异控制算法进程，同时动态调节惯性权重。
Twice Gaussian mutation controlled the algorithm process. Inertia weight was adjusted dynamically.
GPSO可在每次迭代中自适应地得到惯性权重，有效帮助算法克服了早熟的缺点。
At each iteration, GPSO can obtain the inertia weight auto-adapted to help the algorithm overcome precocious shortcoming effectively.
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