Search - mutation in matlab

Search - mutation in matlab - List

[AI-NN-PR] 差别算法matlab源码 DL : 0: 粒子群优化算法(PSO)是一种进化计算技术(evolutionary computation).源于对鸟群捕食的行为研究 PSO同遗传算法类似，是一种基于叠代的优化工具。系统初始化为一组随机解，通过叠代搜寻最优值。但是并没有遗传算法用的交叉(crossover)以及变异(mutation)。而是粒子在解空间追随最优的粒子进行搜索。详细的步骤以后的章节介绍同遗传算法比较，PSO的优势在于简单容易实现并且没有许多参数需要调整。目前已广泛应用于函数优化，神经网络训练，模糊系统控制以及其他遗传算法的应用领域-Particle Swarm Optimization (PSO) is an evolutionary technology (evolutionary computation). Predatory birds originated from the research PSO with similar genetic algorithm is based on iterative optimization tools. Initialize the system for a group of random solutions, through iterative search for the optimal values. However, there is no genetic algorithm with the cross- (crossover) and the variation (mutation). But particles in the solution space following the optimal particle search. The steps detailed chapter on the future of genetic algorithm, the advantages of PSO is simple and easy to achieve without many parameters need to be adjusted. Now it has been widely used function optimization, neural networks, fuzzy systems control and other genetic algorithm applications
Date : 2025-12-24 Size : 16kb User :
[AI-NN-PR] gatbx-origin1 DL : 0: matlab中遗传算法的通用函数，如：选择、交叉、变异等常用算子的遗传算法程序-matlab genetic algorithm in the generic function, such as: selection, crossover and mutation operators, such as commonly used genetic algorithm procedure
Date : 2025-12-24 Size : 33kb User : 熊梅西
[AI-NN-PR] GAforTSP DL : 0: 遗传算法求解TSP问题,采用轮盘赌选择方法,部分匹配交叉算子,交换变异设计.-Genetic Algorithm for TSP problem, using roulette wheel selection method, partially matched crossover operator and exchange mutation design.
Date : 2025-12-24 Size : 5kb User : 底欣
[AI-NN-PR] ga1 DL : 0: 遗传算法程序说明: fga.m 为遗传算法的主程序采用二进制Gray编码,采用基于轮盘赌法的非线性排名选择, 均匀交叉,变异操作,而且还引入了倒位操作!-Description of the procedures for genetic algorithms: fga.m main program for the genetic algorithm using binary Gray encoding, roulette wheel based on the law of non-linear ranking selection, uniform crossover and mutation operations, but also the introduction of the inversion operation!
Date : 2025-12-24 Size : 3kb User : hexing
[AI-NN-PR] genetic-algorithm DL : 0: 自然计算中遗传算法的各个程序，matlab环境下开发的源代码。best.m 求种群中适应度最大的值 calfitvalue.m 计算每个个体的适应度 calobjvalue.m 适应度函数 crossover.m 交叉变换 decodebinary.m 将二进制数转换成十进制数 decodechrom.m 将二进制数转换成十进制数 initpop.m 产生初始种群 mutation.m 变异 selection.m 选择合适的个体进行复制 main.m 主函数 -Nature of each genetic algorithm calculation procedures, matlab environment with source code. best.m find the largest population in the fitness value of calfitvalue.m calculated for each individual' s fitness calobjvalue.m fitness function crossover.m cross-conversion decodebinary.m Converts a binary number into decimal number decodechrom.m Converts a binary number into decimal number initpop.m generate initial population mutation.m variation selection.m select the appropriate individual to copy main.m primary function
Date : 2025-12-24 Size : 3kb User : 王芳
[AI-NN-PR] MATLAB DL : 0: 遗传算法（Genetic Algorithm）是模拟达尔文生物进化论的自然选择和遗传学机理的生物进化过程的计算模型，是一种通过模拟自然进化过程搜索最优解的方法，它最初由美国Michigan大学J.Holland教授于1975年首先提出来的，并出版了颇有影响的专著《Adaptation in Natural and Artificial Systems》，GA这个名称才逐渐为人所知，J.Holland教授所提出的GA通常为简单遗传算法（SGA）。 -In artificial intelligence, an evolutionary algorithm (EA) is a subset of evolutionary computation, a generic population-based metaheuristic optimization algorithm. An EA uses some mechanisms inspired by biological evolution: reproduction, mutation, recombination, and selection. Candidate solutions to the optimization problem play the role of individuals in a population, and the fitness function determines the environment within which the solutions "live" (see also cost function). Evolution of the population then takes place after the repeated application of the above operators. Artificial evolution (AE) describes a process involving individual evolutionary algorithms EAs are individual components that participate in an AE.
Date : 2025-12-24 Size : 46kb User : 李际超
[AI-NN-PR] TSP-GA.zip DL : 0: 旅行商问题（TSP）是一个经典的优化组合问题，本个案列采用遗传算法来求解TSP问题，进行了选择、交叉、变异算子的设计，并通过MATLAB对算法进行了实现，附有详细的说明和代码。,The traveling salesman problem (TSP) is a classic combination optimization problem, in this case the column using a genetic algorithm to solve TSP problem selection, crossover and mutation operator design and realization by MATLAB algorithm, with detailed description and code.
Date : 2025-12-24 Size : 867kb User : ZHENG