pso 中文意思是什麼

pso 解釋
粒子群演算法
  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. Optimization of ordnance urgent transportation decision based on pso

    的軍械緊急調運決策優化
  3. 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。
  4. 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。
  5. Pso idea is an optimization technique inspired by swarm intelligence and theory in general such as bird flocking, fish schooling and even human sacial behavior

    粒子群優化演算法（ particleswarmoptimization簡稱pso ）是一種基於群智能的演化計算技術，源於對鳥群覓食過程中的遷徙和聚集的模擬。
  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. 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 ） 。
  9. By using pso method, the optimal control input signal is obtained and the optimal trajectory of the nonholonomic motion planning can be found

    利用粒子群演算法確定最優控制輸入信號，得到了系統非完整運動的優化軌跡。
  10. Structural reliability and sensitivity analysis of random variables based on pso

    的結構可靠度及隨機變量敏感性分析
  11. Structural damage detection based on pso

    一種檢測渦旋壓縮機渦旋盤的新方法
  12. Analysis of the bidding strategy of power producers with non - cooperative game theory based on pso

    基於供給函數均衡模型的區域電力現貨市場模擬分析
  13. On the basis of analysis of factors impacting on earthwork allocation and transportation, a new kind of earthwork allocation and transportation method based on ant algorithm ( aa ) and particle swarm optimizer ( pso ) is presented in this paper, and it has the advantages of being able to consider nonlinear restrictions and uncertain factors

    摘要本文分析了水利工程中土石方調運的影響因素及其特點，提出了一種基於螞蟻演算法和粒子群演算法的土石方調運優化方法。
  14. New pso algorithm for minlp problems

    用粒子群優化改進演算法求解混合整數非線性規劃問題
  15. 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。
  16. Secondly, in order to improve the local searching capability, the modified pso ( mpso ) which jumps according to probability is introduced, and the mud based on mpso is proposed

    然後為提高演算法的局部尋優能力，提出了按概率突跳的粒子群優化演算法，同樣運用到了多用戶檢測中，提出了基於突跳粒子群優化演算法的多用戶檢測器。
  17. Pso find optimal regions of complex search spaces through the interaction of individuals in a population of particles

    它利用一個粒子群搜索解空間，每個粒子表示一個被優化問題的解，通過粒子間的相互作用發現復雜空間中的最優區域。
  18. A complex particle swarm optimization ( cpso ) algorithm, which combines the advantages of method of complex ( mc ) and particle swarm optimization ( pso ), is put forward to solve systems of nonlinear equations, and it can be used to overcome the difficulty in selecting good initial guess for newton ' s method and the inaccuracy of mc and pso due to being easily trapped into local minima for solving systems of nonlinear equations

    摘要結合復形法與粒子群演算法的優點，提出粒子群復形法，用於求解非線性方程組，以克服牛頓法初始點不易選擇的問題，同時克服復形法與粒子群演算法由於易陷入局部極值而導致方程組的解的精度不夠的不足。
  19. Feature weighting methods are researched in this paper. an algorithm called pso - nn that based on nn algorithm is designed to learn every feature ’ s relevant weight

    本文對特徵加權（ featureweighting ）方法進行研究，針對nn演算法提出了特徵權向量學習演算法: pso - nn演算法。
  20. Optimal design of minitype permanent magnet motor based on hybrid algorithm of chaos and pso

    混沌粒子群混合演算法對微型永磁電機的優化設計
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