搜索资源列表
NSGA2-dynamic
- 多目标优化进化算法目前公认效果收敛性最好的算法NSGA2c++源码,具有一般性,可在此基础上继续改进,对实现其他多目标优化算法很有帮助.-Multi-objective optimization evolutionary algorithm is currently the best recognized effect of convergence of the algorithm NSGA2c++ Source, with the general, could be on this basis
DifferentialEvolutionAPracticalApproachtoGlobalOpt
- 这是一本讲微分进化的书,进化算法是以遗传算法为代表的一类随机算法的总称,95年由Rainer Storn和Kenneth Prici提出微分进化方法,比传统进化算法更好更简单,2004年该方法的原创者出版了长达580页的微分进化:一种全局优化的实用方法,本书是英文版,似乎还没有中文版,希望对感兴趣的人有用-This is a book stresses differential evolution, evolutionary algorithm based on genetic algorith
Geneticalgorithm
- 传算法的基本原理、设计方法及其并行实现,以及它在组合优化、机器学习、图像处理、过程控制、进化神经网络-Propagation algorithm of the basic principles, design methods and their parallel implementation, as well as in combinatorial optimization, machine learning, image processing, process control, evoluti
Dynamic
- A New Dynamic Multi-objective Optimization Evolutionary Algorithm
EvolutionStrategy
- 主要介绍了进化策略的原理,并且用matlab进行了仿真。-Mainly introduces the principles of evolutionary strategy, and conducted a simulation using matlab.
PSO
- 粒子群进化算法,标准的源代码程序和实例教程。-Evolutionary particle swarm algorithm, standard procedures and examples of source code tutorial.
ev
- 从其他网站下载的进化算法的matlab源码-Website from other evolutionary algorithm matlab source
ga
- 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),遗传算法简单源程序。-Genetic Algorit
ANN_Training-withES
- Artificial Nueral Network Training using Evolutionary Strategy.
GuoA
- 郭涛算法(GuoA)是基于子空间搜索(多父体重组)和群体爬山法相结合的演化算法。它通过利用少数个体所张成的子空间随机生成新的个体,体现了随机搜索的非凸性。此外,由于GuoA算法采用了单个体劣汰策略,算法在每次演化 迭代中,只把群体中适应性能最差的个体淘汰出局,淘汰压力 较小,既保证了群体的多样性,又可使具有较好适应性的个体能够一直保留。实践证明, GuoA算法具有较好的坚韧性,对于不同的优化问题无须修改算法的参数,而且效率很高,可能同时找到多个最优解。-Guo Tao algorithm
MelanieMitchellAnIntroductiontoGeneticAlgorithms.
- to learn the use evolutionary algorithms in matlab
GA_NSGA-II
- Develop the NSGA-II or SPEA2 multiobjective evolutionary algorithms to solve the multiobjective optimization problems.-Develop the NSGA-II or SPEA2 multiobjective evolutionary algorithms to solve the multiobjective optimization problems.
SocialEvolutionaryProgramming
- 社会演化算法是一种新型的进化算法。这是基于社会演化算法的PID控制器参数整定的程序。学习遗传算法和进化算法的都有借鉴作用- Social Evolutionary Programming (SEP) to solve this problem. SEP is developed from Genetic Algorithm (GA), inherits the advantage of GA and other algorithms, and has better convergence rat
QEAsolvePackage
- 最近两年比较流行的量子进化算法(QEA),能够求解一般的优化问题。算例是一个典型的背包问题(离散二值问题)。-The more popular the last two years the quantum evolutionary algorithm (QEA), be able to solve the general optimization problems. An example is a typical knapsack problem (discrete binary problem
QEAsolveOptimization
- 最近两年流行的量子进化算法程序,能够优化一下基本的问题,本程序是基于一个连续的极值问题。-The last two years the popular quantum-inspired evolutionary algorithm process, to optimize the basic questions about this program is based on a continuous extremal problem.
DEELMNN
- 利用差分演化优化极限学习机神经网络的matlab源代码,涉及2个matlab程序-evolutionary extreme learning machine, differential evolution
yiqun
- 蚁群算法是一种用来在图中寻找优化路径的机率型技术,该算法具有许多优良的性质,具有一种新的模拟进化优化方法的有效性和应用价值, 是一种求解组合最优化问题的新型通用启发式方法,可以解决一维静态优化问题甚至多维动态组合优化问题。 -Ant colony algorithm is a method used to find optimal path in the graph of the probability-based technology, the algorithm has many goo
GEATbx_Intro_Algorithmen_v38
- Introduction Evolutionary Algorithms: Overview, Methods and Operators.
pso-ppt-sample
- 微粒群优化算法 (PSO) 是一种进化计算技术 , 由Eberhart博士和kennedy博士于1995年提出。微粒群优化算法的基本思想是通过群体中个体之间的协作和信息共享来寻找最优解。 -Particle Swarm Optimization (PSO) is an evolutionary computation technique, by Dr. Eberhart and Dr. kennedy made in 1995. Particle Swarm Optimization Alg
Co-Evolutionary-Algorithm
- Presentation of Co-evolutionary Algorithm