進化演算法 的英文怎麼說

中文拼音 [jìnhuàyǎnsuànfǎ]
進化演算法 英文
evolution algorithms ea
  • 進 : 進構詞成分。
  • 演 : 動詞1 （演變; 演化） develop; evolve 2 （發揮） deduce; elaborate 3 （依照程式練習或計算） drill;...
  • 算 : Ⅰ動詞1 （計算數目） calculate; reckon; compute; figure 2 （計算進去） include; count 3 （謀劃;計...
  • 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...
  • 進化 : evolution
  1. Firstly, this paper deeply studied the simulated evolution theory, demonstrated the feasibility of resolving the optimization problems in the thermodynamic control systems with simulated evolution theory, and through the analysis of the calculability of this theory, created the general frame of the simulated evolution algorithm and created the theoretical base for building the evolution optimizing architecture of thermodynamic control systems

    首先，對模擬進化理論進行深入研究，說明了運用模擬進化理論解決熱力控制系統優化問題的可行性，並通過對模擬進化理論的可計算性分析，建立了模擬進化演算法通用框架，為建立熱力控制系統進化優化體系建立了理論基礎。
  2. The experimental results show that the method can not only detect the fuzzy edge and exiguous edge correctly, but also improve the searching efficiency of fuzzy clustering algorithm based on tea evidently

    實驗結果表明，該演算法不僅具有很強的模糊邊緣和微細邊緣檢測能力，而且可以提高基於人工免疫進化演算法的模糊聚類演算法的搜索效率。
  3. Edm has some remarkable advantages over traditional models, includes using implicit causal models, self - learning capacity, weak dependence on domain knowledge, wide applicability, robustness, self - adaptability, and population - based searching, etc. tracing back its intrinsical ideas, edm is just making use of the nature ' s decision making strategy, natural selection, to solve the decision making problems faced by human or the intelligent agents

    進化決策主要利用了進化演算法與形式化計算模型相結合所具備的自動建模能力，它具有隱式因果模型、自學習、弱知識依賴、應用廣泛、穩健性、自適應和群體搜索等優勢。追根溯源，進化決策的基本思想正是利用大自然的決策機制（自然選擇）來解決客觀世界所提出的決策問題，而自然進化又是已知的能力最強的問題求解范型。
  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. The first part comprises industrial pta oxidation process modeling, residual fluid catalytic cracking process modeling, complex distillation modeling and analysis, the application of pta oxidation process soft - sensor technology. in the second one, the infeasibility degree based genetic algorithm is proposed to handle constrained optimization problem in engineering cases and the neighborhood and archive based genetic algorithm and its variant are proposed to treat the multi - objective optimization problem. with that, the pta oxidation process is regarded as a benchmark for the application of the proposed multi - objective optimization genetic algorithm

    論文內容分為兩部分，第一部分對包括三個典型的工業過程， pta氧化反應器、渣油催化裂化反應系統和復合式精餾塔進行分析、建模以及pta氧化過程的軟測量工程實施；第二部分分別提出了基於進化演算法解決工業過程中普遍存在的約束優化問題和多目標優化問題的過程優化演算法? ?基於不可行度選擇遺傳演算法和基於鄰域和存檔操作遺傳演算法，並利用該演算法對工業pta氧化過程操作進行多目標優化研究。
  6. Other evolutionary algorithms attempt to mimic lamarckian evolution, where behavior as a survival mechanism can be transferred between generations, and there are even evolutionary programs that write themselves for a particular purpose

    其它的進化演算法試圖模擬拉馬克的進化論，在他看來，行為是一種生存的機制，可以在兩代之間傳遞，甚至有一些進化程序是出於某種目的而自然出現的。
  7. Firstly, we introduced the main idea, the formalized description, and the basic flow of co - evolution algorithm. then, from the point of pattern analyzation, we established the mathematics model of the multi - population co - evolution algorithm based on pattern replicator equation of the single population genetic algorithm, and made the theoretical analysis and compare for the method of best choice and the method of random choice of the co - evolution algorithm. we put forward a new method for the individual fitness evaluation, and validated the performance of the new method by the simulation experiment

    首先，在介紹了協進化演算法的核心思想、形式化描述和基本演算法流程的基礎上，從模式分析角度出發，建立了基於模式復制方程的多群體協進化演算法數學模型，對協進化演算法中的最優選擇法和隨機選擇法進行了理論分析與比較，提出了一種新的個體適應度評價方法，並通過模擬實驗驗證了新方法的效率。
  8. The results show the improved aca can be used to solve the continued problem, and the formula whose parameter is optimized by the improved aca can simulate the primary data better than those whose parameter are optimized by other optimizing methods except the immune evolutionary algorithm ( iea ), and the improved aca can get almost the same result with less optimization scale and shorter optimization time than iea

    結果表明，改進的螞蟻演算法可以成功用於暴雨強度公式的參數優化，並且在實驗採用的各種優化演算法優化參數得到的暴雨強度公式擬合原始數據的效果比較中只有免疫進化演算法在優化過程中迭代次數和迭代規模都要大得多的情況下才和改進的螞蟻演算法差不多，而比其它的優化方法都要好。
  9. The co - evolution algorithm is applied to the optimization problem, and a new optimization system and algorithm frame of designing of mixed model flow manufacturing is established

    在混合流水生產系統優化設計中引入協同進化演算法，建立了一種新的混合流水生產系統的優化體系與演算法框架。
  10. The paper details the objective, types and present research of production scheduling, discusses the current research state of the flow shop scheduling and the relative algorithm of this type of problem, pinpoints existing disadvantages, and then provides the generalization of ordinal coding of genetic algorithm and genetic computing element based on the order

    本文詳細介紹了生產作業調度問題的目標、類型及研究現狀，並著重就流水型作業調度問題的研究現狀和該類問題的數學模型與相關演算法，如啟發式方法、進化演算法、鄰域搜索方法等進行了探討，指出了存在的問題。
  11. An improved evolutionary algorithm based on heuristic rules for flow shop scheduling

    基於啟發式規則的新型進化演算法在流水車間調度中的應用
  12. The re suits show the present method is more accurate and reliable than other methods

    分析結果表明，在搜索斜坡滑裂面問題上遺傳進化演算法較其它搜索演算法具有準確性和可靠性的優勢。
  13. The characteristics of quantum computing and the mechanism of immune evolution are analyzed and discussed. inspired by the mechanism in which immune cell can gradually accomplish affinity maturation during the self - evolution process, a immune evolutionary algorithm based on quantum computing ( mqea ) is proposed. the algorithm can find out optimal solution by the mechanism in which antibody can be clone selected, memory cells can be produced, similar antibodies can be suppressed and immune cell can be expressed as quantum bit ( q - bit ). it not only can maintain quite nicely the population diversity than the classical evolutionary algorithm, but also can help to accelerate the convergence speed and converge to the global optimal solution rapidly. the convergence of the mqea is proved and its superiority is shown by some simulation experiments in this paper

    分析和探討了量子計算的特點及免疫進化機制，並結合免疫系統的動力學模型和免疫細胞在自我進化中的親和度成熟機理，提出了一種基於量子計算的免疫進化演算法.該演算法使用量子比特表達染色體，通過免疫克隆、記憶細胞產生和抗體相似性抑制等進化機制可最終找出最優解，它比傳統的量子進化演算法具有更好的種群多樣性、更快的收斂速度和全局尋優能力.在此不僅從理論上證明了該演算法的收斂，而且通過模擬實驗表明了該演算法的優越性
  14. Abstract : the characteristics of quantum computing and the mechanism of immune evolution are analyzed and discussed. inspired by the mechanism in which immune cell can gradually accomplish affinity maturation during the self - evolution process, a immune evolutionary algorithm based on quantum computing ( mqea ) is proposed. the algorithm can find out optimal solution by the mechanism in which antibody can be clone selected, memory cells can be produced, similar antibodies can be suppressed and immune cell can be expressed as quantum bit ( q - bit ). it not only can maintain quite nicely the population diversity than the classical evolutionary algorithm, but also can help to accelerate the convergence speed and converge to the global optimal solution rapidly. the convergence of the mqea is proved and its superiority is shown by some simulation experiments in this paper

    文摘:分析和探討了量子計算的特點及免疫進化機制，並結合免疫系統的動力學模型和免疫細胞在自我進化中的親和度成熟機理，提出了一種基於量子計算的免疫進化演算法.該演算法使用量子比特表達染色體，通過免疫克隆、記憶細胞產生和抗體相似性抑制等進化機制可最終找出最優解，它比傳統的量子進化演算法具有更好的種群多樣性、更快的收斂速度和全局尋優能力.在此不僅從理論上證明了該演算法的收斂，而且通過模擬實驗表明了該演算法的優越性
  15. Vehicle scheduling problem based on dna evolutionary algorithm

    進化演算法的車輛調度問題
  16. By introducing distributed evolution to deb ' s nsga - ii, a distributed multiobjective evolutionary algorithm was given. it was tested on five difficult multiobjective optimization test problems, and the result shows that distributed evolution does improve the performance of the algorithm

    給出了一種分散式的多目標進化演算法，它是用分散式進化方式對deb的nsga -的改進，用五個困難的多目標優化測試問題對該演算法的測試表明這種改進明顯的提高了演算法的性能。
  17. Then this paper discusses the following three research emphasis : 1. in parts, diversity - guided evolutionary algorithms which is applied in the path planning of robots avoids the prematurely convergence

    然後討論了本文以下三個方面的研究重點： 1 、在移動機器人全局路徑規劃中採用多樣性指導進化演算法，它在一定程度上解決了早熟現象。
  18. Finally, for the definite mechanism and indefinite size of industrial robots ' executor as well as the size ^ optimization goal, the mathematic model is set up to optimize the executor ' size with using complex optimization method. next, for the optimized executor, the desired trajectory and planning goal, the kinematics model and proper referent and motive coordinates systems are set up. by making use of the result of the previous motion analysis, genetic algorithm is applied to the trajectory planning of executor

    最後，對于結構給定而構件尺度未定的工業機器人執行機構，先根據機構尺度優化目標，建立數學模型、用復合形法進行構件尺度優化；再根據給定的期望軌跡和規劃目標，建立數學模型，利用復指數變換法對執行機構進行運動分析的結果，採用進化演算法對工業機器人進行軌跡規劃。
  19. On the basis of distributed multiobjective evolutionary algorithm, the nondominated sorting and crowding multiobjective handling mechanism was introduced to distributed coevolutionary mdo algorithm, and the multiobjective distributed coevolutionary mdo algorithm was formed

    在分散式多目標進化演算法研究的基礎上，將非優超排序和排擠的多目標處理機制引入分散式協同進化mdo演算法中，形成了多目標的分散式協同進化mdo演算法。
  20. It also apply an evolutionary algorithm ? ? particle swarm optimization ( pso ) on the problem

    並將一種新的進化演算法? ?粒子群游優化演算法（ pso ） ，應用於暫態穩定極限計算。
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