搜索资源列表
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退火算法,运用退火算法解决函数优化等问题,运用遗传算法解决学生宿舍分配问题。-Annealing algorithms, the annealing algorithm to solve the function optimization using genetic algorithm to solve the problem of allocation of student hostels.
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遗传算法是一种很重要的算法,对于初学者来说很有帮助-Genetic algorithm is a very important algorithms, very helpful for beginners
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现代优化算法包括 遗传算法 退火算法.代码基于matlab 可以直接运行,有图示说明-Modern optimization algorithms, including genetic algorithm annealing algorithm code based on Matlab can be directly run, there is illustrated
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对线性系统的辨识,使用遗传算法实现,并得出图形-The identification of linear systems, the use of genetic algorithms to achieve, and draw graphics
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使用遗传算法的神经网络分类,可以较好的实现(Neural network classification using genetic algorithms)
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wolf calculated Lyapunov exponent, Genetic algorithms using MATLAB path planning, Including the final calculation of the compressed image peak signal to noise ratio and compression of the source.
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遗传算法是计算数学中用于解决最佳化的搜索算法,是进化算法的一种。进化算法最初是借鉴了进化生物学中的一些现象而发展起来的,这些现象包括遗传、突变、自然选择以及杂交等。遗传算法通常实现方式为一种计算机模拟。对于一个最优化问题,一定数量的候选解(称为个体)的抽象表示(称为染色体)的种群向更好的解进化。(Genetic algorithm is used to solve optimization search algorithm in computational mathematics, is a k
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各种PID控制源代码,包括神经网络、粒子群、遗传算法等职能算法的PID控制。(Various PID control source code, including neural networks, particle swarm, genetic algorithms and other functions of the algorithm PID control.)
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利用遗传算法求极值,简单介绍遗传算法的操作流程,更准确的了解遗传算法(Using Genetic Algorithm to Calculate Extrema, Briefly Introduce the Operational Process of Genetic Algorithm, and Know the Genetic Algorithm More Accurately)
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