Description: 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 Platform: |
Size: 5120 |
Author:连宙辉 |
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Description: 这是遗传算法进行函数优化的程序，可以运行成功，需要的就下吧-This is the source code of genetic algorithm for function optimization, it can run ,down it if you need it. Platform: |
Size: 21504 |
Author:wlr |
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Description: 本文采用C++开发遗传算法，并由次算法解决最短路算法，函数最优化算法，取得了良好的效果。-this paper, C development of genetic algorithms, meeting with the shortest path algorithm for solving algorithms, function optimization algorithm, achieved good results. Platform: |
Size: 477184 |
Author:高路新 |
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Description: 基于遗传算法和神经网络的黑箱函数优化举例matlab程序-based on genetic algorithms and neural network as a black box function optimization procedures for Matlab Platform: |
Size: 2048 |
Author:张鹏 |
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Description: 大家好，这是一个基于粒子群优化算法的函数优化问题的MATLAB源码，希望能给大家提供帮助-Hello everyone, this is a particle swarm optimization algorithm based on function optimization problems MATLAB source code, I hope everyone can help Platform: |
Size: 759808 |
Author:邓高峰 |
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Description: 用蚂蚁群算法 编写的函数优化 matlab程序-Ants swarm optimization with the preparation of procedures for the function optimization matlab Platform: |
Size: 2048 |
Author:博击长空 |
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Description: 微粒群优化算法(Particle Swarm Optimization,PSO算法)源于鸟群和鱼群群体运
动行为的研究，是一种新的群体智能优化算法，是演化计算领域中的一个新的分支。它
的主要特点是原理简单、参数少、收敛速度较快，所需领域知识少。该算法的出现引起
了学者们极大的关注，已在函数优化、神经网络训练、组合优化、机器人路径规划等领
域获得了广泛应用，并取得了较好的效果。尽管粒子群优化算法发展近十年，但无论是
理论分析还是实践应用都尚未成熟，有大量的问题值得研究。
-Particle swarm optimization (Particle Swarm Optimization, PSO algorithm) from groups of birds and fish movement behavior, is a new swarm intelligence algorithm, in the field of evolutionary computation is a new branch. Its main feature is simple in principle, few parameters, convergence is faster, less domain knowledge required. The algorithm brought the scholars are of great concern, has been in function optimization, neural network training, combinatorial optimization, robot path planning has been widely used applications, and achieved good results. Despite the development of particle swarm optimization nearly a decade, but both theory and practice applications are not yet mature, a large number of issues worth studying. Platform: |
Size: 602112 |
Author:赵 |
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Description: 人工免疫算法在函数优化中的应用,这篇论文比较偏理论，理解起来较费力-Artificial immune algorithm in function optimization applications, this paper compares the theoretical side, more effort to understand Platform: |
Size: 84992 |
Author:宋旸 |
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Description: 遗传算法在函数优化中的应用研究，通过实例介绍遗传算法的具体应用方法等-Genetic algorithms in function optimization, applied research, through the specific example to illustrate the application of genetic algorithm methods Platform: |
Size: 1502208 |
Author:yu tianhao |
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Description: 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.) Platform: |
Size: 33792 |
Author:FZenjoys |
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Search - function optimization