Description: UMDA. a kind of estimation of distribution algorithm , which is the improvement of genetic algorithm-UMDA. A kind of estimation of distribution algorithm, which is the improvement of genetic algorithm Platform: |
Size: 47771 |
Author:sunxiaodian |
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Description: UMDA. a kind of estimation of distribution algorithm , which is the improvement of genetic algorithm-UMDA. A kind of estimation of distribution algorithm, which is the improvement of genetic algorithm Platform: |
Size: 47104 |
Author:sunxiaodian |
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Description: EM算法，基于期望最大化原则进行密度估计-EM algorithm, based on the expectation maximization of the principle of density estimation Platform: |
Size: 3072 |
Author:丁宏锴 |
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Description: 本程序实做MLP(Multi-layer perceptron)算法，使用者可以自行设定训练数据集与测试数据集，将训练数据集加载，在2、3维下可以显示其分布状态，并分别设定键节值、学习率、迭代次数来训练其类神经网络，最后可观看辨识率与RMSE（Root Mean squared error）来判别训练是否可以停止。-This procedure is to do MLP (Multi-layer perceptron) algorithm, the user can set their own training data set and test data sets, the training data set is loaded, in the 2,3-dimensional display of their distribution, and were set key section of the value of learning rate, number of iterations to train the neural network can watch the final recognition rate and the RMSE (Root Mean squared error) to determine whether the training can stop. Platform: |
Size: 1213440 |
Author:楊易 |
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Description: 多种概率分布的拟合函数集合
本算法包括最大似然估计，最小二乘估计，基于EM算法的多种混合高斯分布估计，EM算法测试实例，绘制每种分布的plot函数。非常有参考价值！-Fitting a wide range of probability distribution functions including the collection of this algorithm maximum likelihood estimation, least squares estimation, based on the EM algorithm estimate a mixture Gaussian distribution, EM algorithm for the test examples, each mapping the distribution of the plot function. Have reference value is! Platform: |
Size: 21504 |
Author:lcp |
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Description: 分布估计算法（EDA）讲义，29页PPT
1. 从GA到 EDA
2. 链接学习与模型
3. 连续EDA
4. EDA 与玻耳兹曼分布
5. 资源
-estimation of distribution algorithm（EDA）tutorial
1. from the GA to the EDA
2. Linking learning and models
3. Continuous EDA
4. EDA with Boltzmann distribution
5. other Resources Platform: |
Size: 199680 |
Author:陈雷 |
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Description: 分布估计算法的PBIL算法源码。新型的进化算法。-The resource of the PBIL algorithm among Estimation of Distribution Algorithms is uploaded. Estimation of Distribution Algorithms is a novel type of evolutionary algorithms. Platform: |
Size: 1024 |
Author:方晓平 |
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Description: 动态K-S检验边缘分布的copula 分布估计算法- Marginal distribution in copula estimation of distribution algorithm based dynamic K-S test Platform: |
Size: 4096 |
Author:赵慧 |
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Description: 静态K-S检验下的copula 分布估计算法边缘分布的研究- Marginal distribution in copula estimation of distribution algorithm based static K-S test Platform: |
Size: 4096 |
Author:赵慧 |
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Description: 主要介绍了分布估计算法方面关于熵的介绍，实现最大熵分布估计算法-Mainly introduces the estimation of distribution algorithm on entropy is introduced, the realization of maximum entropy estimation of distribution algorithm
Platform: |
Size: 892928 |
Author:钟冬军 |
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Description: 分布估计算法基础的函数描述，适合初学者,介绍分布估计算法的基础知识，有MATLAB例子帮助读者理解-Estimation of distribution algorithm based function description, suitable for beginners, introduces the basic knowledge of the estimation of distribution algorithm, MATLAB examples to help readers understand Platform: |
Size: 282624 |
Author:jiao |
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Description: 分布估计算法优秀硕士论文，详细介绍了算法的过程及参数选择，适合初学者学习该算法-Estimation of distribution algorithms outstanding master thesis, introduces in detail the process and parameter selection algorithm, suitable for beginners to learn the algorithm, Platform: |
Size: 1477632 |
Author:jiao |
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Description: 解决多目标优化问题的算法,主要基于概率模型的建立-RM-MEDA: A Regularity Model Based Multiobjective Estimation of Distribution Algorithm Platform: |
Size: 50176 |
Author:崔波 |
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Description: 分布估计算法应用于解决流水车间调度模型是的研究代码-Estimation of distribution algorithm is applied to solve the flow shop scheduling model is the code for research Platform: |
Size: 117760 |
Author:wangguangchen |
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Description: In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs.
This algorithm is a member of the ant colony algorithms family, in swarm intelligence methods, and it constitutes some metaheuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his PhD thesis,[1][2] the first algorithm was aiming to search for an optimal path in a graph, based on the behavior of ants seeking a path between their colony and a source of food. The original idea has since diversified to solve a wider class of numerical problems, and as a result, several problems have emerged, drawing on various aspects of the behavior of ants. From a broader perspective, ACO performs a model-based search [3] and share some similarities with Estimation of Distribution Platform: |
Size: 14336 |
Author:ibra |
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Description: continuous ACO.
In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs.
This algorithm is a member of the ant colony algorithms family, in swarm intelligence methods, and it constitutes some metaheuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his PhD thesis,[1][2] the first algorithm was aiming to search for an optimal path in a graph, based on the behavior of ants seeking a path between their colony and a source of food. The original idea has since diversified to solve a wider class of numerical problems, and as a result, several problems have emerged, drawing on various aspects of the behavior of ants. From a broader perspective, ACO performs a model-based search [3] and share some similarities with Estimation of Distribution Platform: |
Size: 7168 |
Author:ibra |
Hits:
Description: In computer science and operations research, the ant colony optimization algorithm (ACO) is a probabilistic technique for solving computational problems which can be reduced to finding good paths through graphs.
This algorithm is a member of the ant colony algorithms family, in swarm intelligence methods, and it constitutes some metaheuristic optimizations. Initially proposed by Marco Dorigo in 1992 in his PhD thesis, the first algorithm was aiming to search for an optimal path in a graph, based on the behavior of ants seeking a path between their colony and a source of food. The original idea has since diversified to solve a wider class of numerical problems, and as a result, several problems have emerged, drawing on various aspects of the behavior of ants. From a broader perspective, ACO performs a model-based search and share some similarities with Estimation of Distribution Algorithm. Platform: |
Size: 48128 |
Author:reyhooon
|
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