particle swarm optimization 中文意思是什麼

particle swarm optimization 解釋
粒子群優化
  • particle : n 1 顆粒，微粒；微量，極少量。2 【物、數】粒子，質點。3 【語法】虛詞，不變詞〈冠詞、副詞、介詞、...
  • swarm : n 1 （昆蟲的）群，蜂群；【生物學】浮遊單細胞（生物）群，遊走孢子。2 大群；大堆。vi 1 蜂擁成群（而...
  • optimization : n. 最佳化，最優化。
  1. To solve the capacitated dynamic lot - sizing problem in group technology cell, a method based on binary particle swarm optimization ( pso ) algorithm and immune memory mechanism was proposed and its implementation was illustrated in detail

    摘要為求解基於成組單元有能力約束的生產批量計劃問題，提出了一種基於二進制粒子群演算法和免疫記憶機制相結合的方法，並闡明了該方法的具體實現過程。
  2. Optimal calibration of ship degaussing system using stochastic particle swarm optimization

    採用隨機微粒群演算法的艦船消磁系統優化調整
  3. Particle swarm optimization for hot strip mill scheduling

    微粒群演算法及其在熱軋生產調度中的應用
  4. Inspired by the idea of hybrid optimization algorithms, this paper proposes two hybrid quantum evolutionary algorithms ( qea ) based on combining qea with particle swarm optimization ( pso )

    摘要將量子進化演算法（ qea ）和粒子群演算法（ pso ）互相結合，提出了兩種混合量子進化演算法。
  5. An improved pso ( particle swarm optimization ) algorithm is presented which well addresses slow convergence speed and low calculation precision in the basic pso algorithm

    摘要提出了一種改進的粒子群演算法，很好地解決了基本粒子群演算法中易陷入局部最優的缺點。
  6. Particle swarm optimization ( pso ) is inspired by social behavior of bird flocking or fish schooling. it is a population - based, self - adaptive search optimization technique. pso is simple in concept, few in parameters, and easy in implementation

    粒子群優化演算法（ particleswarmoptimization ， pso演算法）源於鳥群和魚群群體運動行為的研究，是一種基於種群搜索策略的自適應隨機演算法，是進化計算領域中的一個新的分支。
  7. Particle swarm optimization ( pso ) algorithm is a computation intelligence technique, inspired by social behavior of birds flocking. pso algorithm possesses the advantages of simplified, rather quick convergence speed, global optimization performance, and less controlling parameters, et al

    粒子群演算法是一種源於鳥群捕食行為的計算智能技術，具有演算法簡單、收斂速度較快、全局優化能力較強、控制參數較少等優點。
  8. A study of loess collapsibility by combining least squares support vector machines with particle swarm optimization algorithm

    組合最小二乘支持向量機與粒子群優化演算法研究黃土濕陷性
  9. Si aims at understanding the collective behavior of swarm insects. we browse briefly its concepts, characteristics and major research areas : sorting behavior, ant colony optimzation ( aco ) and particle swarm optimization ( pso )

    我們先介紹了群體智能的特點，研究方法和主要研究的3個問題：分揀行為，螞蟻演算法和粒子群體優化（ pso ） 。
  10. Response surface has been built based on bp neural network with relationship of maximum of spinning force variety, material parameters and power spinning process parameters established and optimum achieved by using particle swarm optimization algorithm hence optimization of tube power spinning process parameters

    摘要以bp神經網路為基礎構建響應曲面，建立材料參數、筒形件強力旋壓工藝參數等和旋壓力最大變化值之間的關系，並用粒子群優化演算法求解，獲得符合優化條件的最優解，從而實現筒形件強力旋壓工藝參數的優化。
  11. Ant colony and particle swarm optimization algorithm - based solution to multi - objective flexible job - shop scheduling problems

    基於蟻群粒子群演算法求解多目標柔性調度問題
  12. A particle swarm optimization with step - accelerating mutation operator

    含步長加速變異運算元的微粒群演算法
  13. Application analysis on reservoir operation by particle swarm optimization

    粒子群優化演算法在水庫調度中的應用分析
  14. Particle swarm optimization algorithm and its application in extracting roots of complicated chemical equations

    微粒群優化演算法及其在復雜化學方程求根中的應用
  15. Optimal power flow using particle swarm optimization and non - stationary multi - stage assignment penalty function

    基於粒子群優化演算法和動態調整罰函數的最優潮流計算
  16. Adaptive filter design based on particle swarm optimization algorithm

    基於自適應變異粒子群優化演算法的自適應濾波器設計
  17. Particle swarm optimization based on rotate surface transformation

    基於旋轉曲面變換的粒子群優化方法
  18. Tsapso : a hybrid search algorithm of tabu search and annealing particle swarm optimization for weapon - target assignment

    基於禁忌退火粒子群演算法的火力分配
  19. The particle swarm optimization ( pso ) algorithm was invented by eberhart and kennedy in 1995 as a parallel optimization. it comes of the behavior of birds searching food

    粒子群優化演算法是由美國心理學家jameskennedy和電氣工程師russelleberhart在1995年共同提出的一種并行演化計算技術，源於對一個簡化社會模型鳥群捕食系統的模擬。
  20. The search space is divided into many small areas, and each area is given a certain pheromone value. according to the state transition rules, the artificial ants move to the next solution which is generated randomly or calculated by particle swarm optimization. local search strategy is also added into psaco so that the search speed and precision is enhanced

    該演算法首先將連續對象定義域平均分成許多邊緣相互重疊的小區域，區域的稠密程度決定了演算法解的精度，每個區域賦予一定的信息素值;螞蟻根據狀態轉移規則在隨機生成的可行解與利用微粒群演算法得出的可行解之間選擇下一步要去的位置;引入局部尋優策略，加強近似最優解鄰域內的局部搜索，提高搜索速度和精度。
分享友人
分享到 Line

分享到臉書