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Description: 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 algorithm to represent a class of random algorithm collectively, 95 by Rainer Storn and Kenneth Prici proposed differential evolution approach, better than the traditional evolutionary algorithm simpler, 2004 The method of the originators of the publication of up to 580 of the differential evolution: A practical method for global optimization, this book is the English version seems to have been the Chinese version, in the hope that people interested in useful
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Author: plow |
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Description: 微粒群算法[PSO ] 是由Kennedy 和Eberhart等于1995 年开发的一种演化计算技术, 来源于对鸟群捕食过程的模拟。PSO同遗传算法类似，是一种基于叠代的优化工具，但与遗传算法使用遗传操作子进行优化不同，利用群体中各个体之间的“协作”与“竞争”关系，根据自身及其竞争者的飞行经验，调整自己的行为。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] are equal by Kennedy and Eberhart in 1995 developed an evolutionary computing technology, from preying on the birds of the simulation process. PSO with genetic algorithm is similar to an iterative optimization-based tool, but the use of genetic algorithms and genetic manipulation of different sub-optimize the use of groups between the various entities within the " collaboration" and " competitive" relationship, according to themselves and their competition the flying experience, adjust their behavior. Comparison with genetic algorithms, PSO has the advantage of being simple and easy and did not realize the need to adjust the parameters much. Has been widely applied to function optimization, neural network training, fuzzy system control, as well as other genetic algorithm applications.
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Author: wzy |
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Description: 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, evolutionary neural network
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Size: 9216 |
Author: 鲁明 |
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Description: A New Dynamic Multi-objective Optimization Evolutionary Algorithm
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Author: Jacky Gao |
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Description: 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.
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Size: 25600 |
Author: zhangzongzhi |
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Description: 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.
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Size: 11264 |
Author: jia |
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Description: book evolutionary computing
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Size: 17376256 |
Author: hvyhv |
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Description: 从其他网站下载的进化算法的matlab源码-Website from other evolutionary algorithm matlab source
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Size: 1430528 |
Author: ggb |
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Description: 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 Algorithm (Genetic Algorithm) is a simulation of the biological theory of evolution Darwin' s natural selection and genetic mechanism of the process of biological evolution computing model is a natural evolutionary process by simulating the optimal solution search methods, it was first introduced by J. Holland United States University of Michigan Professor in 1975, first put forward, and published influential monographs " Adaptation in Natural and Artificial Systems" , GA gradually known the name, J. Holland, Professor of GA are usually made by a simple genetic algorithm (SGA ), a simple genetic algorithm source code.
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Author: 周武静 |
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Description: Artificial Nueral Network Training using Evolutionary Strategy.
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Author: eda_wiz |
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Description: 基于局部搜索能力强、收敛速度快的特点,首先初始化一个没有子种群的全局种群,再在全局种群中采用迭代搜索,并对其中的个体进行聚类,当聚类簇中的个体数目达到规定的最小规模时形成一个子种群,然后在各子种群中进行迭代搜索并重新进行聚类,从而提高进化过程中种群的多样性,增强算法跳出局部最优的能力.该算法基于weka，用于weka拓展功能，需要 weka算法包支持。-Based on the local search ability, the characteristics of fast convergence, first initialize a sub-population of the overall population, then the overall population in the iterative search, and clustering of the individuals, when the clustering of individual cluster achieve the required minimum number of the scale of the formation of a subset of the population, and then in the sub-populations in the iterative search and re-clustering to improve the evolutionary process of population diversity, enhancement algorithm' s ability to jump out of local optimum.
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Size: 5120 |
Author: zhangrui |
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Description: 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 (GuoA) is based on the sub-space search (more than the reorganization of the parent body) and combination groups climbing the evolutionary algorithm. It is through the use of a small number of individual sub-space by Zhang generate a new random individual, reflects the random search of the non-convexity. In addition, the algorithm uses a single GuoA poor individual survival strategies, the evolution algorithm in each iteration, only to groups of individuals to adapt to the worst performance out of the game, out less stressful, not only to ensure the diversity of the groups, but also could have better adaptability to the individual has been retained. Practice has proved that, GuoA algorithm has good tenacity, and for different optimization algorithm is no need to change the parameters, and efficient, you may find more than one optimal solution at the same time.
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Size: 3072 |
Author: zhao |
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Description: 量子进化算法论文，详尽介绍该算法的原理及实验结果-Quantum evolutionary algorithm papers, detailed descriptions of the principle of the algorithm and experimental results
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Size: 369664 |
Author: 向健 |
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Description: to learn the use evolutionary algorithms in matlab
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Size: 1884160 |
Author: prakash |
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Description: 此pdf格式文本资料是关于进化合成模式识别系统的理论书籍-Evolutionary Synthesis of Pattern Recognition Systems
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Size: 13666304 |
Author: Y.Meng |
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Description: 摘 要:提出一种新的基于Pareto多目标进化免疫算法(PMEIA)。算法在每一代进化群体中选取最优非支配抗体保存到记忆细胞文档中 同时引入Parzen窗估计法计算记忆细胞的熵值,根据熵值对记忆细胞文档进行动更新,使算法向着理想Pareto最优边界搜索。此外,算法基于点在目标空间分况进行克隆选择,有利于得到分布较广的Pareto最优边界,且加快了收敛速度。与已有算法相比, PMEIA在收敛性、多样性,以及解的分布性方面都得到很好的提高。-Abstract:This paperproposed a new pareto-based multi-object evolutionary mi mune algorithm(PMEIA). PMEIA selected
optmi alnon-dominated antibodieswhichwere then reserved inmemory cellarchive, and introducedParzenwindow to calculate
entropy ofmemory cells. Updated thememory cell archive according to entropy ofmemory cells. This guarantees the conver-
gence to the true Pareto fron.t Moreover, the performance of clone selection was dependent on distribution in the objective
space, whichwas favorable forgetting awidely spreadPareto frontand mi proving convergence speed. Comparedwith the exis-
ted algorithms, the obtained solutions ofPMEIA havemuch betterperformance in the convergence, diversity and distribution.
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Size: 276480 |
Author: 王飞 |
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Description: 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.
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Size: 3072 |
Author: Su Yu-Jiun |
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Description: 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 rate and the computation efficiency than GA.
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Size: 8192 |
Author: wangjin |
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Description: 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 problems).
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Size: 1024 |
Author: 王潮 |
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Description: 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.
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Size: 2048 |
Author: 王潮 |
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