mutation operator 中文意思是什麼
mutation operator
解釋
變異運算元-
Introduction of prepotency operator in the initialize population step and the improved mutation operator accelerate the convergence process, and the introduction of new operator in forming new population step avoid converging in local optimum, and promote the ability of global convergence
演算法在初始化種群階段引入了「優生」運算元，以及改進的變異操作使演算法的收斂速度大大提高；在形成新種群階段引入新的運算元避免了局部早熟，提高了全局收斂能力。 -
In this paper, a genetic algorithm was presented to solve the problem of the searching of the optimal coalition structure. we designd one - dimension chromosome coding structure and the corresponding improved uniformity crossover operator and the heuristic mutation operator
我們給出了一種求解最佳聯盟結構的gas演算法，設計出了一種簡單的一維自然數染色體編碼結構和改進的均勻交叉運算元以及啟發式變異運算元。 -
Crossover is implemented using arithmetic crossover operator. then unsymmetrical mutation is conducted using the new mutation operator which can expand the scope of chromosome gene value, at the same time, the chromosome with the highest fitness values are retained for each iteration. a lot of experiments are implemented to obtain the optimized initial weighs and bias
生成了三維矩陣表示的染色體，進行了聯賽選擇，利用算術交叉運算元進行了交叉運算，利用構造的新的變異運算元，進行了非均勻變異，同時保留了每次進化運算后最優的適應值，通過大量實驗，實現了遺傳演算法優化bp網路的初始權值和閾值的目的。 -
A particle swarm optimization with step - accelerating mutation operator
含步長加速變異運算元的微粒群演算法 -
At first, in order to prevent the premature convergence of genetic algorithm effectively, the author brings forward a novel dyadic floating - point supplementary mutation operator. then, simulating the natural evolution, the author presents a novel topology, unoriented - connected topology, for parallel genetic algorithm. in the end, an interval decomposed optimization method is brought forward for ipga, which can improve the optimization performance of the algorithm
為提高演算法的性能，作者對遺傳演算法進行三種改進：首先，為克服遺傳演算法早熟收斂，作者提出一種新的二元浮點補碼變異運算元；其次，模擬生物自然進化模式，為并行遺傳演算法提出了一個新的并行拓撲結構- - - -無定向拓撲連接；最後，作者提出一種區間分解優化思想，來提高對最優解的搜索能力。 -
Based on the single genetic algorithms and the features of the distribution network reconfiguration, this dissertation makes a further study on such aspects as selection operator, crossover operator, mutation operator, termination conditions and etc, thus, puts forward improved genetic algorithms. the dissertation makes certain study on the optimization reconfiguration model of distribution network. it puts forward a multi - objective model and according to the theory of variable weight coefficients transforms the multi - objective problem into a single - objective one
針對目前遺傳演算法在配電網路重構應用中的不足，論文著重從選擇運算元、交叉運算元、變異運算元和收斂準則等方面進行了改進，把最優保存策略和兩兩競爭相結合的方法作為新的選擇運算元，採用隨最優個體相對保留代數自適應變化的交叉和變異運算元，把最優個體最少保留代數作為演算法的終止條件。 -
In order to enhance the applying efficiency of cl, the cause of premature convergence in binary - coded genetic algorithms ( gas ) is analyzed in this dissertation. the drawback of conventional mutation operator in preventing premature convergence is subsequently pointed out. whereafter, a genetic algorithm, which can be implemented via general logic gate circuit, is proposed
為了提高計算智能的應用效率，本文分析了二進制遺傳演算法中早熟收斂的成因，指出了傳統的變異運算元在防止早熟收斂方面的不足，提出了一種能有效預防早熟現象的二元變異運算元，並在此基礎上提出了一種便於用常規邏輯門電路實現的遺傳演算法。 -
Study on improvement of mutation operator in evolutionary programming and evolutionary strategies
進化規劃和進化策略中變異運算元的改進研究 -
The main research work of dissertation can be concluded as follows : 1. two kinds of hybrid strategies of genetic algorithms and tabu search are discussed systematically in this paper. the idea of tabu search is introduced to improve crossover operator and mutation operator of genetic algorithms for the first strategy, while tabu search is executed to a certain proportional selected individuals in the population after genetic evolution of every generation for the second strategy
本文的主要研究成果概括如下: 1 .論文比較系統地探討了遺傳演算法和禁忌搜索演算法的兩種混合策略:第一種是利用禁忌搜索的思想來改進遺傳演算法的交叉運算元和變異運算元;第二種是對每代中交叉變異后得到的新種群中的一定比例的個體進行禁忌搜索處理。 -
The whole colony is divided into some colonies and they have evolution independently. selection operator, crossing operator, mutation operator and some parameters setting are advanced
設計過程中，將整個群體劃分為幾個子群體，各自獨立進化，選擇運算元、交叉運算元和變異運算元以及其他參數都做了相應的改進。 -
To compensate the shortage of the bigger test set of pure ant algorithm, the method of crossing ant algorithm and genetic algorithm is presented. meanwhile, the implementation methods of the objective function, selection operator, crossover operator, and mutation operator are given, and the test results are compared with the results of ant algorithm, based on standard sequential circuits iscas ' 89
為彌補單純採用螞蟻演算法進行測試矢量生成時，測試矢量集過大的缺點，摘要提出了螞蟻演算法和遺傳演算法交叉的測試生成方法，給出了遺傳演算法的目標函數、選擇運算元、交叉運算元、變異運算元的實現方法。 -
This paper, firstly, expatiates the content and sense about optimal design of water supply networks, briefly introduces all optimal methods which have been advanced, analyzes these methods and points out their limitation, summarizes the factors which influence the results in optimal design of water supply networks ; secondly, it introduces the principle of genetic algorithms ( ga ). it takes yearly expenditure converting value as target function and sets up the ga model on optimal design of water supply networks based on sga by means of taking some effective measures on selection operator, crossover operator, mutation operator and some parameters setting ; finally, the ga model is verified by its application on engineering project
本文首先闡述了給水管網優化設計的內容和意義，簡要介紹了已有的優化方法，分析比較了各種優化方法並指出其存在的不足，歸納總結了影響給水管網優化設計結果的各種因素；接著，介紹了遺傳演算法的基本原理，然後在標準遺傳演算法的基礎上，通過對選擇運算元、交叉運算元、變異運算元以及部分參數的設置採取改進措施，並以年費用折算值為目標函數，建立了給水管網優化設計的遺傳演算法模型；最後，通過工程實例驗證了該模型具有一定的理論和應用價值。 -
( 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。 -
Mechanism analysis of mutation operator based on algebraic crossover operator
基於代數雜交運算元的變異運算元機理分析 -
The main research achievements are as follows : a new mutation operator is constructed
主要成果如下:構造了新的變異運算元。 -
Similarity - based crossover - mutation operator and its application to mining classification rules
基於相似度的交叉變異運算元及其在分類規則挖掘中的應用 -
We should specially point out that by the function of the mutation operator, which ensures a stable convergence of the algorithm into a global optimum
需要特別指出的是，通過該變異運算元的作用，可以使演算法穩定地收斂到全局最優解。 -
Through the simulation test, the paper analyses the impact of crossover operator, mutation operator and eliminating near best result operator on the algorithms
通過模擬實驗，本文分析了交叉運算元、變異運算元及近憂淘汰算于對演算法的影響。 -
The advantage of genetic algorithms lies in : to search the best solution for many initial points ; and find the total optimum solution by means of crossover and mutation operator
它從多個初始點開始尋優，藉助交叉和變異運算元來獲得參數的全局最優解。 -
Pso is simple and efficient, so many researchers have been attracted by this algorithm, and furthermore, it converges fast by moving each particle aimed at guides when it deals with single - objective optimization, and these features are important in multi - objective optimization also. from some current research works, we describe a multi - objective particle swarm optimization algorithm ( mopso ) that incorporates the concept of the enhanced - dominance, we present this new concept to update the archive, the archiving technique can help us to maintain a sequence of well - spread solutions. a new particle update strategy and the mutation operator are shown to speed up convergence
目前，國內外已有部分相關研究成果，但是它們在解集分佈性、收斂性方面仍存在不足，在吸取已有成果的基礎上，本文提出了一種改進的多目標粒子群演算法（ mopso ） ，使用我們提出的強支配概念構造外部種群，使解集保持良好的分佈性，同時，通過採用新的全局極值和個體極值的選取方式及採用新的種群更新策略加快解集的收斂，提出基於快速排序的非支配集構造方法加快演算法運行效率。
分享友人