群迭代法 的英文怎麼說

中文拼音 [qúndiědàifǎ]
群迭代法 英文
group interation
  • 群 : Ⅰ名詞（聚在一起的人或物） crowd; group Ⅱ量詞（用於成群的人或物） group; herd; flock
  • 迭 : Ⅰ動詞（輪流; 替換） alternate; change Ⅱ副詞1 （屢次） repeatedly; again and again 2 （及） in tim...
  • 代 : Ⅰ動詞1 （代替） take the place of; be in place of 2 （代理） act on behalf of; acting Ⅱ名詞1 （歷...
  • 法 : Ⅰ名詞1 （由國家制定或認可的行為規則的總稱） law 2 （方法; 方式） way; method; mode; means 3 （標...
  1. The three kinds of construction graph can be applied to optimization problems with different characteristics, and the two kinds of layered construction graph are more suitable for complex multi - stage dynamic decision problems ( cmsddp ) than scg. the clcg defines smaller solution building blocks and is able to perform better in large - scale cmsddps than the blcg. 2. the construction graph of aco algorithms need statically describe the whole solution space ( or discrete solution spa

    （ 2 ）蟻群優化演算法的解構造圖一般要靜態地描述整個解空間（或者是離散化了的解空間） ，對于大規劃動態決策問題，不僅存在描述解空間的困難，而且讓蟻群在迭代過程中始終在整個解空間中進行搜索，搜索性能會很低。
  2. Aim at ubiquitous parallel multi - reservoir structure in our country ' s basin, the universal objective function including coefficient bi embodying a spatial significance difference at different flood control points and variable ai denoting a selection of scheduling mode is established, which provide a valid intervenor interface for flood control consultation decision. according to the real - time requirement, a model of reservoir storage allocation is proposed, which embody basic idea of phasic compensation. passing the dynamic correction to cut down the disadvantageous influence that indetermination result in on the certain degree, joining together the step alternation solving method, this model can maximally consider bias of decision makers, ensure the rationality and practicability of the solutions

    針對我國流域中普遍存在的並聯庫群結構，論文提出包含不同防洪點重要性的系數_ i和選擇調度模式的變量_ i的通用目標函數，為防洪會商決策，提供了有效的人工干預介面，根據實時性要求提出動態分配防洪庫容的庫容分配方法，體現了相機補償的基本思想，通過動態修正在一定程度上可以削減不確定性造成的不利影響，結合分步迭代求解技術，能最大限度體現決策者的偏好，保障解的合理性和可操作性。
  3. The simulation results of a batch process shows that the iterative particle swarm algorithm can solve the robust optimization problems of batch processes effectively if there is no state independent and end - point constraints

    對一個間歇過程的模擬結果證明了迭代粒子群演算法可以有效地解決無狀態獨立約束和終端約束的間歇過程魯棒優化間題。
  4. An iterative particle swarm algorithm is proposed for the robust optimization problem of hatch processes without state independent and end - point constraints, which combines the iteration method and the particle swarm optimization algorithm together

    摘要針對無狀態獨立約束和終端約束的間歇過程魯棒優化問題，將迭代方法與粒子群優化演算法相結合，提出了迭代粒子群演算法。
  5. This thesis suggests a process considered minimizes the population size as similar individuals occur in the fitter members of the population, which helps reduce the execution times for ga by removing the redundancy associated with the saturation effect found in the later generation. this thesis uses a method that adds dynamic penalty terms to the fitness function according to the optimal degree of solutions, so as to create a gradient toward a feasible suboptimal or even optimal solutions. on the basis of the difference of the biggest and the smallest of fitness of individual, modifying the fitness function in order to convergence is a satisfaction

    動態調節種群大小，去掉遺傳演算法在迭代後期搜索產生的過多相似個體，達到減少計算時間的目的；按照解的優劣程度給適應度函數增加一個在ga搜索過程中動態改變的可變罰函數，給搜索最優解創造一個梯度，使遺傳演算法收斂到可行的較優解或最優解；根據適應度值最大和最小個體的差修正適應度函數，使適應度函數值適中不容易造成收斂太快、局部收斂或根本不收斂而變成隨機搜索；為了避免「近親繁殖」採用競爭擇優的交叉操作；利用并行遺傳演算法的思想，提出一種自適應多子種群進化策略；提出人口汰新政策來解決類似甚至相同的個體的情況發生。
  6. Recently, clusters with distributed memory are popular for parallel computing systems, and mpi is the actual standard of message passing programming. therefore, the application of clusters based on mpi to computational electromagnetics is studied in this dissertation. the methods are mom based on the integral equation method in conjunction with the preconditioning technique to speed up the iterative solution and a matrix order reducing method, namely the characteristic basis function method ( cbfm )

    目前，分散式內存的集群系統是并行計算系統的主流系統， mpi是消息傳遞編程實際上的標準，本文即研究了基於mpi的集群技術在計算電磁學中的應用，採用的方法主要是基於積分方程的矩量法，並結合了加速迭代的預條件技術以及一種矩陣降階方法? ? cbf方法。
  7. In the next section of this paper we describe a non - generational ga for multiobjective optimization problems ( mop ). in it the replacement policy is such that an offspring replaces the worst one in the current population only if it is better then it

    在將錯位交叉運算元應用於多目標優化問題求解時，本文提出一種基於非群體迭代型的小生境多目標優化遺傳演算法，即演算法迭代過程中不是更換種群全部或大部分個體，而是每次更新群體中最差的個體。
  8. Based on the idea of linkage identification, piecewise interval correlation by iteration ( pici ) linkage identification based population decomposition algorithm is presented in allusion to the deficiency of existing population decomposition methods in coevolutionary algorithm

    摘要針對已有協同進化演算法種群分割方法的不足，借鑒連接識別思想，提出用分段間隔相關迭代連接識別進行種群分割的演算法。
  9. The improvements in this thesis include the hybrid code method, the method of generation of initial populations, substituting the children for parents by combination of the simulated annealing algorithm and niche, adding some new chromosomes to ensure the population ’ s diversity and using the adaptive probability of crossover and mutation

    本文的改進方案主要涉及混合編碼方式，初始種群的產生方式，採用結合模擬退火演算法和小生境思想的替代策略，迭代過程中添加新染色體，採用自適應交叉、變異概率等。
  10. But, pso convergence ' s speed become slow in latter iterative phase, and pso is easy to fall into local optimization. at present, some scholars improve base pso mostly using 3 methods : disperse algorithm, increase convergence speed, enhance particle ' kinds. in the paper, i put forward 2 methods aiming at local best resutl but not whole best result. i modify base pso using the last method. some scholars put forward times initializations, so i select best result after circulating some times to be a parameter of formula. first, put particle into some small region, and ensure every region having one paticle at least. second, every region ' s particle has probability transfer other regions. although increase running time, enhance particle ' kinds, decrese the probability of convergence far from whole best result. nerms ( network educational resource management system ) is one of the research projects in the science and technology development planning of jilin province. the aim of nerms is to organize and manage various twelve kinds of network educational resources effectively so that people can share and gain them easily and efficiently, so as to quicken the development of network education

    但粒子群演算法仍存在如下不足:首先在多峰的情況下，粒子群有可能錯過全局最優解，遠離最優解的空間，最終得到局部最優解;其次在演算法收斂的情況下，由於所有的粒子都向最優解的方向群游，所有的粒子趨向同一，失去了粒子間解的多樣性，使得後期的收斂速度明顯變慢，同時演算法收斂到一定精度時，演算法無法繼續優化，本文對原始粒子群演算法提出了二點改進方案: 1 .演算法迭代到一定代數后，把此時找到的全局最優解當作速度更新公式的另一參數（本文稱之為階段最優解）再進行迭代; 2 .每次迭代過程中除最優解以外的每個粒子都有一定概率「變異」到一個步長以外的區域，其中「變異」的粒子在每一維上都隨機生成一個步長。
  11. When the genetic algorithm is implemented it is usually done in a manner that involves the following cycle : evaluate the fitness of all of the individuals in the population. create a new population by performing operations such as selection, crossover and mutation on the individuals whose fitness has just been measured. discard the old population and iterate using the new population

    遺傳演算法是通過下面簡要步驟的循環最終獲得優化問題的解的：隨機生成一定數目的個體構成初始群體，計算群體中每個個體的適應度，使用遺傳操作即選擇、交叉、變異運算元產生新一代群體然後代替上?代群體并迭代執行。
  12. An evolutionary iterated local search algorithm with the features of multiple neighborhood structures and population - based evolution is designed to solve the model

    提出了一種基於多個鄰域結構和種群進化策略的進化迭代局部搜索演算法，用於求解該模型。
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