Description: 简洁得模拟退火算法，用来求函数得极值问题，有兴趣得可以看看。里面提出了一个问题，有兴趣得可以做一个实验-concise in simulated annealing algorithm, used to function in extreme demand, are interested they can look at. They raised a question that interested you can do an experiment Platform: |
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Author:张庆 |
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Description: 由于K－均值聚类算法局部最优的特点，而模拟退火算法理论上具有全局最优的特点。因此，用模拟退火算法对聚类进行了改进。20组聚类仿真表明，平均每次对K结果值改进8次左右，效果显著。下一步工作：实际上在高温区随机生成邻域是个组合爆炸问题（见本人上载软件‘k－均值聚类算法’所述），高温跳出局部解的概率几乎为0，因此正考虑采用凸包约束进行模拟聚类，相关工作正在进行。很快将奉献给各位朋友。-as K-means clustering algorithm for optimal local characteristics, and simulated annealing algorithm theory with the characteristics of the global optimum. Thus, simulated annealing algorithm for clustering improvements. Cluster Group of 20 simulations show that the average value of K results improved about eight times, the results are obvious. The next step : In fact, in high temperature generated random neighborhood is a combination of explosives (see my software on the 'k-means clustering algorithm' mentioned above), high-temperature solution of partial out almost zero probability, it is considering the use of convex hull bound for simulation cluster, the work under way . Soon dedication to the ladies. Platform: |
Size: 5120 |
Author:韩磊 |
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Description: 模拟退火算法 模拟退火算法(Simulated Annealing,简称SA算法)是模拟加热熔化的金属的退火过程，来寻找全局最优解的有效方法之一。 模拟退火的基本思想和步骤如下： 设S＝{s1,s2,…,sn}为所有可能的状态所构成的集合， f：S—R为非负代价函数，即优化问题抽象如下： 寻找s*∈S，使得f(s*)＝min f(si) 任意si∈S （1）给定一较高初始温度T，随机产生初始状态S （2）按一定方式，对当前状态作随机扰动，产生一个新的状态S’ S’＝S＋sign(η).δ 其中δ为给定的步长， η为[－1,1]的随机数-simulated annealing algorithm (Simulated Annealing, or SA algorithm) is a simulation of heating molten metal in the annealing process, to find the global optimum one of the effective ways. Simulated Annealing basic ideas and the steps are as follows : S = (s1, s2, ..., sn) for all possible state posed by the pool, f : S-R non-negative cost function, that is abstract optimization problems are as follows : Find S* s, making f (s*) = min f (si) arbitrary si S (1) to set a higher initial temperature T, randomly generated initial state S (2) of a certain form, the current state of random disturbance, have a new state S 'S' = S+ sign (). delta where given for the step, [-1,1] Random Number Platform: |
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Author: |
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Description: 以一个简单的例子说明模拟退火算法的思想。 模拟退火法求函数f(x,y) = 5sin(xy) + x^2 + y^2的最小值，对理解模拟退火算法是一个很好的程序示例。-to a simple example illustrates the simulated annealing algorithm thinking. Simulated Annealing for the function f (x, y) = 5sin (xy) x ^ 2 y ^ 2 minimum, the right understanding of simulated annealing method is a good example of the procedure. Platform: |
Size: 1024 |
Author:小刘 |
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Description: 一种新型的算法，将模拟退火法和遗传算法相结合，用于求解预测问题-A new algorithm, simulated annealing and genetic algorithm are combined to solve the prediction problem for Platform: |
Size: 3072 |
Author:秦朗 |
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Description: 模拟退火算法，基本算法，内附部分说明以及本人学习笔记-Simulated annealing algorithm, the basic algorithm, I am enclosing some notes, and study notes Platform: |
Size: 22528 |
Author:jay |
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Description: 模拟退火算法的MATLAB范例程序！对初步了解的初学者有不错的帮助！-Simulated annealing algorithm MATLAB example program! Preliminary understanding of the beginners have a good help! Platform: |
Size: 139264 |
Author:瞿颜 |
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