Description: 遗传算法(Genetic Algorithm, GA)是近几年发展起来的一种崭新的全局优化算法，它借
用了生物遗传学的观点，通过自然选择、遗传、变异等作用机制，实现各个个体的适应性
的提高。这一点体现了自然界中\"物竞天择、适者生存\"进化过程。1962年Holland教授首次
提出了GA算法的思想，从而吸引了大批的研究者，迅速推广到优化、搜索、机器学习等方
面，并奠定了坚实的理论基础。 用遗传算法解决问题时，首先要对待解决问题的模型结构
和参数进行编码，一般用字符串表示，这个过程就将问题符号化、离散化了。也有在连续
空间定义的GA(Genetic Algorithm in Continuous Space, GACS)，暂不讨论。-genetic algorithm (Genetic Algorithm. GA) is developed in recent years a new global optimization algorithm, it borrows from the biological point of view of genetics, through natural selection, genetic variation, such as mechanisms to achieve the adaptability of various individuals raised. This is reflected in the natural world, "the process of natural selection and survival of the fittest" evolutionary process. In 1962, Professor Holland first proposed the idea of the algorithm, thereby attracting a large number of researchers, to promote rapid optimization, search, machine learning, and to lay a solid foundation in theory. Using genetic algorithms to solve the problem, we must first solve the problem of the treatment of the model structure and coding parameters, general string, Platform: |
Size: 409964 |
Author:冯灿科 |
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Description: Simple GA code (Pascal code from Goldberg, D. E. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning.)
-Simple GA code (Pascal code from Goldberg. D. E. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning.) Platform: |
Size: 39587 |
Author:sunxiaodian |
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Description: 遗传算法(Genetic Algorithm, GA)是近几年发展起来的一种崭新的全局优化算法，它借
用了生物遗传学的观点，通过自然选择、遗传、变异等作用机制，实现各个个体的适应性
的提高。这一点体现了自然界中"物竞天择、适者生存"进化过程。1962年Holland教授首次
提出了GA算法的思想，从而吸引了大批的研究者，迅速推广到优化、搜索、机器学习等方
面，并奠定了坚实的理论基础。 用遗传算法解决问题时，首先要对待解决问题的模型结构
和参数进行编码，一般用字符串表示，这个过程就将问题符号化、离散化了。也有在连续
空间定义的GA(Genetic Algorithm in Continuous Space, GACS)，暂不讨论。-genetic algorithm (Genetic Algorithm. GA) is developed in recent years a new global optimization algorithm, it borrows from the biological point of view of genetics, through natural selection, genetic variation, such as mechanisms to achieve the adaptability of various individuals raised. This is reflected in the natural world, "the process of natural selection and survival of the fittest" evolutionary process. In 1962, Professor Holland first proposed the idea of the algorithm, thereby attracting a large number of researchers, to promote rapid optimization, search, machine learning, and to lay a solid foundation in theory. Using genetic algorithms to solve the problem, we must first solve the problem of the treatment of the model structure and coding parameters, general string, Platform: |
Size: 409600 |
Author:冯灿科 |
Hits:
Description: Simple GA code (Pascal code from Goldberg, D. E. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning.)
-Simple GA code (Pascal code from Goldberg. D. E. (1989), Genetic Algorithms in Search, Optimization, and Machine Learning.) Platform: |
Size: 38912 |
Author:sunxiaodian |
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Description: 遗传算法
遗传算法简称GA(Genetic Algorithm)，在本质上是一种不依赖具体问题的直接搜索方法。遗传算法在模式识别、神经网络、图像处理、机器学习、工业优化控制、自适应控制、生物科学、社会科学等方面都得到应用。在人工智能研究中，现在人们认为“遗传算法、自适应系统、细胞自动机、混沌理论与人工智能一样，都是对今后十年的计算技术有重大影响的关键技术”。-Referred to as genetic algorithm genetic algorithm GA (Genetic Algorithm), in essence is a kind of do not rely on specific issues of direct search method. Genetic algorithm in pattern recognition, neural networks, image processing, machine learning, optimization of industrial control, adaptive control, biological sciences, social sciences and so on have been applied. Research in artificial intelligence, now that the " genetic algorithms, adaptive systems, cellular automata, chaos theory and artificial intelligence, are the next ten years of the computing technology have a major impact on the key technology." Platform: |
Size: 303104 |
Author:sunguili |
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Description: 遗传算法简称GA(Genetic Algorithm)，在本质上是一种不依赖具体问题的直接搜索方法。遗传算法在模式识别、神经网络、图像处理、机器学习、工业优化控制、自适应控制、生物科学、社会科学等方面都得到应用。在人工智能研究中，现在人们认为“遗传算法、自适应系统、细胞自动机、混沌理论与人工智能一样，都是对今后十年的计算技术有重大影响的关键技术”。-Referred to as genetic algorithm GA (Genetic Algorithm), in essence is a kind of do not rely on specific issues of direct search method. Genetic algorithm in pattern recognition, neural networks, image processing, machine learning, optimization of industrial control, adaptive control, biological sciences, social sciences and so on have been applied. Research in artificial intelligence, now that the " genetic algorithms, adaptive systems, cellular automata, chaos theory and artificial intelligence, are the next ten years of the computing technology have a major impact on the key technology." Platform: |
Size: 307200 |
Author:sunguili |
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Description: 遗传算法简称GA(Genetic Algorithm)，在本质上是一种不依赖具体问题的直接搜索方法。遗传算法在模式识别、神经网络、图像处理、机器学习、工业优化控制、自适应控制、生物科学、社会科学等方面都得到应用。在人工智能研究中，现在人们认为“遗传算法、自适应系统、细胞自动机、混沌理论与人工智能一样，都是对今后十年的计算技术有重大影响的关键技术”。-Referred to as genetic algorithm GA (Genetic Algorithm), in essence is a kind of do not rely on specific issues of direct search method. Genetic algorithm in pattern recognition, neural networks, image processing, machine learning, optimization of industrial control, adaptive control, biological sciences, social sciences and so on have been applied. Research in artificial intelligence, now that the " genetic algorithms, adaptive systems, cellular automata, chaos theory and artificial intelligence, are the next ten years of the computing technology have a major impact on the key technology." Platform: |
Size: 176128 |
Author:sunguili |
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Description: 遗传编程
遗传编程,或称基因编程/GP ，是一种从生物演化过程得到灵感的自动化生成和选择计算机程序来完成用户定义的任务的技术。从理论上讲，人类用遗传编程只需要告诉计算机"需要完成什么"，而不用告诉它"如何去完成",最终可能实现真正意义上的人工智能：自动化的发明机器。
-In artificial intelligence, genetic programming (GP) is an evolutionary algorithm-based methodology inspired by biological evolution to find computer programs that perform a user-defined task. It is a specialization of genetic algorithms (GA) where each individual is a computer program. Therefore it is a machine learning technique used to optimize a population of computer programs according to a fitness landscape determined by a program s ability to perform a given computational task. Platform: |
Size: 12288 |
Author:leon |
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Description: Feature selection methods for machine learning algorithms such as SVR, including one filter-based method (CFS) and two wrapper-based methods (GA and PSO). The gridsearch is for the grid search for the optimal hyperparemeters of SVR. The SVM_CV is for the k-fold cross-validation of SVR. All the programs are flexible and could be implemented by the users themselves.-Feature selection methods for machine learning algorithms such as SVR, including one filter-based method (CFS) and two wrapper-based methods (GA and PSO). The gridsearch is for the grid search for the optimal hyperparemeters of SVR. The SVM_CV is for the k-fold cross-validation of SVR. All the programs are flexible and could be implemented by the users themselves. Platform: |
Size: 6144 |
Author:Gang Fu |
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Description: gA 算法是机器学习很重要的算法，目前正在开发研究阶段，其算法是仿照人类而生的。-gA machine learning algorithm is very important to the algorithm, is currently developing the research stage, the algorithm is modeled on the human born. Platform: |
Size: 145408 |
Author:楚天 |
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Description: 基本遗传算法的MATLAB语言源程序。（遗传算法的应用范围极其广泛，它可应用于函数优化、组合优化、生产调度问题、自动控制、机器人学、图像处理、人工生命、遗传编程以及机器学习等领域。）-Basic genetic algorithm matlb language sourc-e code. (Genetic algorithm extremely broad range of applications, it can be applied to function optimization, combinatorial optimization, production scheduling problem, automatic control, robotics, image processing, artificial life, genetic programming, as well as machine learning and other fields.)
Platform: |
Size: 3072 |
Author:derek |
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Description: The aim of Genetic Programming (GP) is to extend genetic forms from
Genetic Algorithm (GA) to the expression of trees and graphs and to apply
them to the synthesis of programs and the formation of hypotheses or concepts. Researchers are using GP to attempt to improve their software for the
design of control systems and structures for robots. Platform: |
Size: 7568384 |
Author:Levan |
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Description: 遗传算法（Genetic Algorithm）是一类借鉴生物界的进化规律（适者生存，优胜劣汰遗传机制）演化而来的随机化搜索方法。它是由美国的J.Holland教授1975年首先提出，其主要特点是直接对结构对象进行操作，不存在求导和函数连续性的限定；具有内在的隐并行性和更好的全局寻优能力；采用概率化的寻优方法，能自动获取和指导优化的搜索空间，自适应地调整搜索方向，不需要确定的规则。遗传算法的这些性质，已被人们广泛地应用于组合优化、机器学习、信号处理、自适应控制和人工生命等领域。它是现代有关智能计算中的关键技术。-Genetic Algorithm (Genetic Algorithm) is a type of reference biological evolution law (survival of the fittest, survival of the fittest genetic mechanism) random search method evolved. It was first proposed by the United States J.Holland professor in 1975, its main feature is the direct object of the structure of the operation, continuity of derivation and function defined does not exist have a global implicit inherent parallelism and better optimization capability with probability of optimization method that can automatically obtain and guide optimized search space, the search direction adaptively adjust the rules do not need to determine. These properties GA, has been widely used in combinatorial optimization, machine learning, signal processing field, adaptive control and artificial life. It is a modern computing on smart key technology. Platform: |
Size: 2048 |
Author:tyy |
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Description: 本人机器学习大作业，详细阐述遗传算法。matlab环境下，针对具体例子，用遗传算法求极值。-My machine learning assignments, detailed in this paper, the genetic algorithm.Matlab environment, in view of the specific example, using genetic algorithm for extremum. Platform: |
Size: 3530752 |
Author:liu |
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Description: 遗传算法优化的极限学习机模型 采用水仙花基本特征数据集 效果比单纯的ELM模型要好(The effect of using daffodils basic feature data set in the extreme learning machine model optimized by genetic algorithm is better than that of ELM model only.) Platform: |
Size: 10240 |
Author:cassdlina |
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