adaptive crossover 中文意思是什麼
adaptive crossover
解釋
自適應交叉-
In this genetic algorithm, each member in a supply chain alliance has a self - adaptive ability to changes in environment in the genetic process through designing crossover probability and mutation probability
該演算法設計了自適應交叉概率和變異概率，使每個個體在遺傳過程中對環境變化具有自適應調節能力。 -
Simple genetic algorithm gets local minimization too easily and converges slowly. to solve these problems, adaptive crossover rate that has reverse hyperbolic rel ation with the numbers of iteration is designed, and adaptive mutation rate that has reverse proportion to the distances of parents and reverse exponential relat ion to the numbers of iteration is put forward. the practical simulation results show that the adaptive ga has greater convergence speed and larger probability o f getting the best solution
簡單遺傳演算法存在著收斂速度慢、易陷入局部極小等缺陷.針對這些缺陷，本文設計出隨相對遺傳代數呈雙曲線下降的自適應交換率，並提出與父串間的相對歐氏距離成反比、隨相對遺傳代數指數下降的自適應變異率.實例驗證表明，具有自適應交換率和變異率的遺傳演算法在收斂速度和獲得全局最優解的概率兩個方面都有很大的提高 -
The method not only can coordinate evolutionary process inside each population by using an adaptive regulation of crossover and mutation operators, but also can advance the formation of - best design by using adaptive adjustment of the competition frequency between populations
該方法不僅運用交叉運算元和變異運算元的自適應調節技術協調種內進化過程，而且通過種間競爭頻率的自適應調節促進最優個體的生成。 -
2 ) for the ability of searching, a formula of adaptive crossover rate decreasing with the increasing of genetic generation
2 ）設計出餘弦下降的自適應交叉率公式以改善遺傳演算法搜索能力。 -
Perfection and adjustment according to system properties, it combines genetic algorithms with fuzzy control, detailed analyzes the problem of designing fuzzy controller and proposes two advanced schemes : first scheme : the change - of - variables are emerged into input variables of the simple fuzzy controllers of oil feeding pump system as one variable, and one pi block is connected after output of fuzzy controllers, consequently the structure of the improved fuzzy controller is analyzed, finally genetic algorithms with adaptive probabilities of crossover and mutation is applied to optimize membership functions and fusing factors of the fuzzy controllers, and the simulation results of before and after optimization are compared
由於在模糊控制器的設計過程中存在較多的人為因素，為了實現根據系統特性對模糊規則和隸屬函數進行自動修正、完善和調整，本文將遺傳演算法和模糊控制結合起來，並針對前面設計的模糊控制器中所存在的問題進行了詳細分析，提出了兩種改進方案： 1在簡單模糊控制器的輸入變量中加入了變量變化率的信息，即將輸入變量和變量的變化率融合為一個輸入量，並在模糊控制器的輸出端加入比例、積分環節，然後分析了這種改進后的模糊控制器的解析結構，最後採用改進后的自適應遺傳運算元的遺傳演算法對模糊控制器中的隸屬函數和融合因子進行優化，並將優化前後的結果作了比較和分析。 2 -
( 3 ) an adaptive crossover operator, an adaptive mutation operator and a multiple and variable elitist operator are proposed to enhance the reliability and efficiency of ga
（ 3 ）提出了自適應雜交、自適應突變和多重動態優選等遺傳運算元，旨在提高ga的可靠性和效率。 -
So the improvement, such as the self - adaptive fitness function combined with the penalty function methods, self - adaptive crossover probability and the bp operator enlightened by neutral network, especially the bp network to improve the local optimal capacity were used
其次結合懲罰函數法對適應度進行了優化。採用自適應交叉概率。受神經網路中bp演算法的啟示，構造bp運算元，提高小種群遺傳演算法的局部搜索尋優能力。 -
When carrying on the distribution network reactive power coordination optimization, the discrete values of compensation capacitor are obtained using adaptive crossover step genetic algorithm on the basis of consideration of bo th network reconfiguration based on ts algorithm and compensation capacitors continuous variable optimization, accordingly the high efficiency and global optimal solution of network coordination reactive optimization are achieved
對配電網路無功綜合優化，本文提出在同時考慮基於禁忌演算法的配電網路重構和補償電容器連續變量優化的基礎上，再應用自適應交叉步長遺傳演算法進行離散變量求解，獲得補償電容器的離散量值。 -
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。 -
Besides, proposing an adaptive variation factor to keep the diversity of population, and a novel crossover rule to widen the distribution space of children generations also effectively modified the sga
提出的相應技術包括：採集種群多樣性指標用以調整變異概率；改進交叉運算元，避免子代收縮，並提高其適應度；新增powell尋優運算元，加速局部搜索。
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