Search - Optimization of process by genetic algorithm

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[AI-NN-PR] MYGA_2 DL : 0: 遗传算法解决双变量的函数最优化问题，有按钮的界面，用bc所编，生动模拟遗传进化过程-genetic algorithm to solve the two- variable optimization function, the button interface, using bc prepared by the vivid simulation of the process of genetic evolution
Date : 2025-12-28 Size : 5kb User : 连宙辉
[AI-NN-PR] intelligent_control_modle DL : 0: 本人调试的大作业（源程序模型+论文），主要包括PID控制、模糊控制、神经网络控制、遗传算法优化神经网络控制（使用了遗传工具箱GAOT）对同一系统所作的仿真比较，并加入饱和、死区、时滞等非线性后的响应，具体的分析比较过程论文中写的很详细。-I debug a big operation (source model+ Thesis), including PID control, fuzzy control, neural network control, genetic algorithm optimization of neural network control (using a genetic toolbox GAOT) on the same system simulation by the comparison, and to join saturation, dead zones, such as nonlinear time-delay after the response, the specific analysis of the comparison process paper written in great detail.
Date : 2025-12-28 Size : 277kb User : hcnden
[AI-NN-PR] yichuansuanfa DL : 0: 遗传算法，是模拟达尔文的遗传选择和自然淘汰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.遗传算法是一类可用于复杂系统优化的具有鲁棒性的搜索算法-Genetic algorithm, is a simulation of Darwinian natural selection to genetic selection and biological evolution of the computing model is a natural evolutionary process by simulating the optimal solution search methods. Is a kind of genetic algorithm can be used for optimization of complex systems is robust The search algorithm
Date : 2025-12-28 Size : 1kb User : 曹睿
[AI-NN-PR] genetic DL : 0: 此文档是遗传算法原理加源代码。生物的进化是一个奇妙的优化过程，它通过选择淘汰，突然变异，基因遗传等规律产生适应环境变化的优良物种。遗传算法是根据生物进化思想而启发得出的一种全局优化算法。 -This document is the principle of genetic algorithm source code increases. Biological evolution is a wonderful optimization process, it eliminated by choosing a sudden variation of genetic and other changes in the law to adapt to the environment arising from the fine species. Genetic algorithm is based on ideas of biological evolution and the inspiration derived from a global optimization algorithm.
Date : 2025-12-28 Size : 9kb User : sunguili
[AI-NN-PR] Genetic_Algorithm DL : 0: 利用matlab编写的一些简单函数优化的遗传算法程序～-Matlab prepared to use some simple function of the genetic algorithm optimization process ~
Date : 2025-12-28 Size : 4kb User : 何洪举
[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 : 2025-12-28 Size : 46kb User : 李际超
[AI-NN-PR] rengongyiqun DL : 0: 蚁群算法(ant colony optimization, ACO)，又称蚂蚁算法，是一种用来在图中寻找优化路径的机率型算法。它由Marco Dorigo于1992年在他的博士论文中提出，其灵感来源于蚂蚁在寻找食物过程中发现路径的行为。蚁群算法是一种模拟进化算法，初步的研究表明该算法具有许多优良的性质。针对PID控制器参数优化设计问题，将蚁群算法设计的结果与遗传算法设计的结果进行了比较，数值仿真结果表明，蚁群算法具有一种新的模拟进化优化方法的有效性和应用价值。-Ant colony algorithm (ant colony optimization, the ACO), also called ant algorithm, is a kind of used to type the probability of finding optimal path algorithm in the picture. It by Marco Dorigo in 1992 in his PhD thesis is put forward, its inspiration the path in the process of ants searching for food. Ant colony algorithm is a kind of simulated evolutionary algorithm, preliminary studies show that the algorithm has many good properties. For PID controller parameters optimization design problem, the result of the ant colony algorithm was designed with the genetic algorithm by comparing the results of the numerical simulation results show that the ant colony algorithm is a new kind of simulated evolutionary optimization method is effective and applied value.
Date : 2025-12-28 Size : 2kb User : 王强
[AI-NN-PR] Function optimization algorithm DL : 0: 遗传算法提供了求解非线性规划的通用框架，它不依赖于问题的具体领域。遗传算法的优点是将问题参数编码成染色体后进行优化，而不针对参数本身，从而不受函数约束条件的限制；搜索过程从问题解的一个集合开始，而不是单个个体，具有隐含并行搜索特性，可大大减少陷入局部最小的可能性。而且优化计算时算法不依赖于梯度信息，且不要求目标函数连续及可导，使其适于求解传统搜索方法难以解决的大规模、非线性组合优化问题。(Genetic algorithm provides a general framework for solving nonlinear programming, which does not depend on the specific problem domain. The advantage of genetic algorithm is that the problem parameters are encoded into chromosomes for optimization, rather than the parameters themselves. The search process starts from a set of problem solutions, rather than a single individual, and has the implicit parallel search feature, which can greatly reduce the possibility of falling into the local minimum. Moreover, the algorithm does not rely on gradient information and does not require the objective function to be continuous and differentiable, which makes it suitable for solving large-scale and nonlinear combinatorial optimization problems that are difficult to be solved by traditional search methods.)
Date : 2025-12-28 Size : 33kb User : FZenjoys