適應度函數 的英文怎麼說

中文拼音 [shìyīngdùhánshǔ]
適應度函數 英文
fitness function
  • 適 : 形容詞1 （適合） fit; suitable; proper 2 （恰好） right; opportune 3 （舒服） comfortable; well Ⅱ...
  • 應 : 應動詞1 （回答） answer; respond to; echo 2 （滿足要求） comply with; grant 3 （順應; 適應） suit...
  • 度 : 度動詞[書面語] （推測; 估計） surmise; estimate
  • 函 : 名詞1. [書面語] （匣; 封套） case; envelope 2. （信件） letter 3. （姓氏） a surname
  • 數 : 數副詞（屢次） frequently; repeatedly
  • 適應 : suit; adapt; get with it; fit
  • 函數 : [數學] function函數計算機 function computer; 函數計算器 function calculator; 函數運算 functional operation
  1. Taking gobang as an example, this paper proposes the base scheme for solve game problem by adopting the notion of genetic algorithms instead of search tree, and makes some exploratory work on the design of fitness function, it also provides with requirements for designing fitness function

    以五子棋為例，提出了用遺傳演算法代替搜索樹法解決博弈問題的基本方案，並對適應度函數的設計作了一些有益地探索，給出了設計適應度函數應滿足的必要條件。
  2. Based on natural selection, it executes three same and simple genetic operators : selection, crossover and mutation. under the leading of fitness value, it makes an efficient searching in complex spaces until acquiring the best result

    它基於自然選擇的原理，通過循環執行相同的、簡單的選擇、雜交和變異三種遺傳操作，並在適應度函數值的引導下對復雜的解空間進行有效地搜索，直到獲得最優的解。
  3. It is applicable to various structural distribution networks. while resolving the " large area restoration ", the genetic algorithm execute three same and simple genetic operators : selection, crossing and mutating. it make a self - adaptable and probability overall searching under the leading of fitness value in the whole searching scale until acquiring the best result

    在求解網路故障后重構問題時，互動式模糊遺傳演算法通過循環執行相同的、極其簡單的選擇、雜交和變異三種遺傳操作，並在適應度函數值的引導下在搜索空間進行自適應概率性全局搜索，直至獲得全局最優解。
  4. In order to calculate difficult transportation cost between plants and distribution centers in the fitness value function, flow prediction algorithm was presented to find an minimum - cost flow patterns on an network composed of plants, consolidation centers and distribution centers with concave transportation costs and to obtain the appropriate fitness value

    為了解決適應度函數中的工廠與分銷中心之間的運輸成本計算困難的問題，提出了流預測演算法，用於確定產品在工廠、集貨中心和分銷中心構成的凹費用流網路中的最優運輸路徑，進而獲得適應度函數值。
  5. In this text, we first do some research on the genetic algorithm about clustering, discuss about the way of coding and the construction of fitness function, analyze the influence that different genetic manipulation do to the effect of cluster algorithm. then analyze and research on the way that select the initial value in the k - means algorithm, we propose a mix clustering algorithm to improve the k - means algorithm by using genetic algorithm. first we use k - learning genetic algorithm to identify the number of the clusters, then use the clustering result of the genetic clustering algorithm as the initial cluster center of k - means clustering. these two steps are finished based on small database which equably sampling from the whole database, now we have known the number of the clusters and initial cluster center, finally we use k - means algorithm to finish the clustering on the whole database. because genetic algorithm search for the best solution by simulating the process of evolution, the most distinct trait of the algorithm is connotative parallelism and the ability to take advantage of the global information, so the algorithm take on strong steadiness, avoid getting into the local

    本文首先對聚類分析的遺傳演算法進行了研究，討論了聚類問題的編碼方式和適應度函數的構造方案與計算方法，分析了不同遺傳操作對聚類演算法的性能和聚類效果的影響意義。然後對k - means演算法中初值的選取方法進行了分析和研究，提出了一種基於遺傳演算法的k - means聚類改進（混合聚類演算法） ，在基於均勻采樣的小樣本集上用k值學習遺傳演算法確定聚類數k ，用遺傳聚類演算法的聚類結果作為k - means聚類的初始聚類中心，最後在已知初始聚類數和初始聚類中心的情況下用k - means演算法對完整數據集進行聚類。由於遺傳演算法是一種通過模擬自然進化過程搜索最優解的方法，其顯著特點是隱含并行性和對全局信息的有效利用的能力，所以新的改進演算法具有較強的穩健性，可避免陷入局部最優，大大提高聚類效果。
  6. Firstly, in this thesis, we discuss the development of one - dimensional cutting stock problems and other well - known algorithms about them, summarize the basic principle of genetic algorithms, and analyze the effect of coding, fitness function, crossover operators and mutation operators in the genetic process of genetic algorithms

    本文首先介紹了一維下料問題的研究概況及其已有的著名演算法，綜述了遺傳演算法的基本原理和方法，分析了遺傳演算法的編碼、適應度函數、交叉和變異運算元在整個遺傳演算法的運算過程中的作用。
  7. Based on the genetic algorithm ' s global searching capability with probability regulation and euclid ' s space distance metric to settle multi - objective, the algorithm that integrates multi - objective ' s decision - making into the modified genetic algorithm to solute the optimal model with discrete variables and multi - objective is proposed. during the algorithm ' s design, the euclid ' s space distance metric is proposed to transform the multi - objective problem into single objective problem. and some modified measure to fitness function and crossover probability and mutation probability are used to improve the performance of the algorithm and avoid premature convergence

    演算法設計過程中，利用歐幾里德空間距離準則和罰函數法，將含有約束條件的多目標規劃問題轉化為無約束的單目標優化問題；針對簡單遺傳演算法出現的早熟，構造隨進化代數動態調整適應度的適應度函數和隨個體適應度自適應調整的交叉、變異概率；提出比例選擇與精英保留策略相結合的選擇、兩點交叉和簡單變異的改進遺傳演算法。
  8. Better segmentation effect can be attained by coding gray levels of pixels as eigenvector, taking advantage of histogram entropy principles function as fitness function, adopting ranking selection operation, making use of arithmetic crossover and mutation at a certain probability, combining with clustering analysis to initialize clustering center of the population to segment cells image with genetic algorithm

    以像素的灰度值為特徵向量進行編碼，利用直方圖熵法準則函數作為適應度函數，採用基於排名的選擇操作，以一定的概率進行算術交叉和變異，並結合聚類分析設定種群的聚類中心對細胞圖像進行遺傳聚類分割。
  9. During the development, problems of actual layout have been considered, both the method using the experiential value of fitness function to identify the number of the initial rectangle parts and the method of magnifying rectangle parts to eliminate the influence of cutting gap have been advanced

    在開發過程中，全面考慮了實際排樣所面臨的種種問題，提出了用適應度函數經驗值來估計初始可排矩形件數目的方法；用矩形件放大的方法來消除切縫對排樣圖的影響。
  10. After a short - term load forecasting method based analogous and linear extrapolation is proposed, the load forecast and the priority of equipment action are led into static reactive power optimization. the aim function is constructed for the practical situation of power system. on the basis of traditional genetic algorithm the fitness function and the holding of population diversity are improved

    在提出基於相似日和線性外推的短期負荷預測新方法的基礎上，將負荷預測和設備動作優先級引入靜態無功優化中，並結合電網實際情況，構造了實用的目標函數，對遺傳演算法的適應度函數和群體多樣性的保持進行了改進，採用鄰域搜索運算元增加遺傳演算法的局部尋優能力。
  11. Orthogonal experimental design method was compared with genetic algorithm for hunting out optimum values, and an optimum method of orthogonal - genetic algorithm testing method that was applicable in greater design variables and unmanageable fit function was presented, and was applied to optimal design of the mechanism and to obtain the optimum scheme of the mechanism ' s geometrical dimensions

    對正交試驗設計法和遺傳演算法的尋優演算法進行分析比較，提出一種設計變量多且適應度函數難求的正交遺傳試驗法的優化方法，將這種方法應用於機構的優化設計中，獲得優化工作空間性能的結構參數方案。
  12. To pick up the convergence speed of traditional genetic algorithm, a modified genetic algorithm is presented, which is based on subsection integer coding, combining stable - state selection strategy with inequality individual and scaling, adaptive recombination according to gene sufficiency, self - adaptive variable step and multi - gene mutation

    將兩幅圖象重疊區域的歸一化差圖象作為搜索空間，定義一個與圖象高相等維數的向量作為染色體，染色體的基因表示每一行圖象中的最優拼接點，採用常用的最小值搜索適應度函數作為視差圖像拼縫搜索的適應度函數。
  13. Explaining the coding scheme, fitness function, ga operator, etc details. the effectiveness is proved by the simulation result of matlab. 3

    詳細闡述了設計思想、編碼方案、適應度函數的選取、遺傳運算元的改進等細節問題，並使用matlab模擬證明該方法的有效性。
  14. By the coding, all first - order rules needed to explore are mapped into the points in genetic space ; ( 2 ) the fitness function, which evaluates the quality of first - order rule. the variation of fir

    （ 2 ）評判一階規則優劣的適應度函數，一階規則適應度的相應變化形成了遺傳空間高低起伏的地貌特徵； （ 3 ）由交叉和變異運算元決定的規則間的鄰接關系，描述了遺傳空間地貌的溝壑或橋梁。
  15. In order to solve the premature problem in strength optimization design of laminate, to combine the part - degenerate operator and adaptive operator is a good idea. poisson ' s ratio is a parameter which measures the volume - changed of objects

    同時針對強度優化的具體問題構造合適的適應度函數，並且通過採用「局部退化運算元」和「自適應運算元」相結合的方法較好地解決了基本遺傳演算法中常見的早熟性收斂問題。
  16. In order to add the resource collected by nerms resource collecting system to database according to its content, we must give a label for each resource. if we just do the work one by one manually, we will find it ' s a tedious job and we must find a new tool to help us, so the resource classifier l

    本文提出一個頻率統計函數，一個基於頻率的分類規則適應度函數以及一個用於分類的打分函數，並把這三個函數結合適用於粒子群演算法的分類規則編碼來更準確的提取規則集，然後通過修改粒子位置更新方程使粒子群演算法適于解決分類規則挖掘問題。
  17. In this algorithm, the unfitness function is chosen as a merit at the beginning of iterative and a new cross operation is designed. in addition, we use a hybrid mutation operation, and make immune operation on individual after mutation operation

    該演算法在迭代初期引入不適應度函數作為評價標準，結合啟發式交叉和邊重組交叉運算元設計了一種新的交叉運算元，採用了模式變異和啟發式變異相結合的混合變異運算元，並對變異后個體進行免疫操作。
  18. This algorithm uses the quotient as the fitness of each individual and employs pseudo - relaxation method to adjust individual solution when it does not satisfy constraining condition any more after genetic operation

    這種方法應用遺傳演算法和準鬆弛方法來得到bam的可行解，以mav和連接權方差之商為個體適應度函數，並應用準鬆弛方法來調整不滿足約束條件的個體。
  19. Genetic algorithm with dual fitness function

    一個具有對偶適應度函數的遺傳演算法
  20. A genetic algorithm with a dual fitness function was proposed

    摘要提出一個具有對偶適應度函數的遺傳演算法。
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