Description: 模拟退火程序:这部分代码是模式识别中结合模拟退火法的特征提取，大家可以对其进行简单的改进会获得更好的效果，比如改变温度表，加上“记忆体”，结合遗传算法等
-simulated annealing procedures : This code is part of pattern recognition in combination with simulated annealing method of feature extraction, you can perform simple improvements will be better results, such as changes in thermometers, the words "memory" combining genetic algorithm Platform: |
Size: 195584 |
Author:天才 |
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Description: 特征点匹配的多种方法，迭代法，遗传算法，退火法，相关归一度法，只是论文的介绍，程序还要自己编的-A variety of feature point matching method, iterative method, genetic algorithm, annealing, related to the time law, only thesis introduction, the program would also like to own the Platform: |
Size: 11260928 |
Author:张晓亮 |
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Description: 关于链式智能体遗传算法用于数值优化和特征选择的论文，可以与我联系相互交流-On the chain-agent genetic algorithm for numerical optimization and feature selection of the papers, you can contact me exchange Platform: |
Size: 1073152 |
Author:李明 |
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Description: 本代码是基于面部感情特征提取的一种遗传算法，-The code is based on the facial feature extraction of the feelings of a genetic algorithm, Platform: |
Size: 4842496 |
Author:yinglun |
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Description: 用遗传算法进行特征选取和svm参数优化的程序。遗传算法工具箱goat已在压缩包 需要安装libsvm就可以直接运行。数据集采用UCI中的german数据集，并完成归一化操作-Genetic algorithm with feature selection and parameter optimization svm procedures. Genetic Algorithm Toolbox in goat need to install libsvm package can be run directly. UCI data sets used in the german data set, and complete normalization operation Platform: |
Size: 139264 |
Author:覃茂运 |
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Description: SVM方法的基本思想是：定义最优线性超平面，并把寻找最优线性超平面的算法归结为求解一个凸规划问题。进而基于Mercer核展开定理，通过非线性映射φ，把样本空间映射到一个高维乃至于无穷维的特征空间（Hilbert空间），使在特征空间中可以应用线性学习机的方法解决样本空间中的高度非线性分类和回归等问题。svm 程序，即支持向量机的代码。-The basic idea of SVM method are: the definition of the optimal linear hyperplane, and the search algorithm for optimal linear hyperplane by solving a convex programming problem. Then based on Mercer nuclear expansion theorem, through a nonlinear mapping φ, the sample space is mapped to a high-dimensional and even infinite dimensional feature space (Hilbert space), so that in the feature space can be applied to solve the linear learning machine method, the sample space The highly nonlinear classification and regression problems. svm procedures that support vector machine code. Platform: |
Size: 117760 |
Author:秀 |
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Description: matlab中编的基于遗传算法的转子故障特征选择的小程序，新手程度，仅供参考-matlab in the series based on genetic algorithm rotor fault feature selection of small programs, novice level, for reference only Platform: |
Size: 222208 |
Author:HUXING |
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Description: This submission contains
(1) Journal Article on Zernike Moments, Genetic Algorithm, Feature Selection and Probabilistic Neural Networks.
(2) MATLAB code to do Feature Selection Using Genetic Algorithm.
NB:
(i) This code is short BUT it works incredibly well since we employed GA Toolbox.
(ii) You can run this code directly on your computer since the dataset herein is available in MATLAB software.
(iii) Please do cite my publication to give credit to me (if you use this code).
The citation is as follows:
BABATUNDE Oluleye, ARMSTRONG Leisa J, LENG Jinsong and DIEPEVEEN Dean (2014). Zernike Moments and Genetic Algorithm: Tutorial and Application. British Journal of Mathematics & Computer Science. 4(15):2217-2236.
Or
BABATUNDE, Oluleye and ARMSTRONG, Leisa and LENG, Jinsong and DIEPEVEEN (2014). A Genetic Algorithm-Based Feature Selection. International Journal of Electronics Communication and Computer Engineering: 5(4) 889 905.-This submission contains
(1) Journal Article on Zernike Moments, Genetic Algorithm, Feature Selection and Probabilistic Neural Networks.
(2) MATLAB code to do Feature Selection Using Genetic Algorithm.
NB:
(i) This code is short BUT it works incredibly well since we employed GA Toolbox.
(ii) You can run this code directly on your computer since the dataset herein is available in MATLAB software.
(iii) Please do cite my publication to give credit to me (if you use this code).
The citation is as follows:
BABATUNDE Oluleye, ARMSTRONG Leisa J, LENG Jinsong and DIEPEVEEN Dean (2014). Zernike Moments and Genetic Algorithm: Tutorial and Application. British Journal of Mathematics & Computer Science. 4(15):2217-2236.
Or
BABATUNDE, Oluleye and ARMSTRONG, Leisa and LENG, Jinsong and DIEPEVEEN (2014). A Genetic Algorithm-Based Feature Selection. International Journal of Electronics Communication and Computer Engineering: 5(4) 889 905. Platform: |
Size: 1434624 |
Author:abdalla |
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Description: 可以动态调节运行环境的参数，遗传算法无功优化，在MATLAB中求图像纹理特征。- Can dynamically adjust the parameters of the operating environment, Genetic algorithm based reactive power optimization, In the MATLAB image texture feature. Platform: |
Size: 6144 |
Author:touqengfao |
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Description: 结合PCA的尺度不变特征变换(SIFT)算法，用MATLAB编写的遗传算法路径规划，是信号处理的基础。- Combined with PCA scale invariant feature transform (SIFT) algorithm, Genetic algorithms using MATLAB path planning, Is the basis of the signal processing. Platform: |
Size: 3072 |
Author:赵鹏 |
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Description: 该代码针对滚动轴承故障振动信号呈现出非线性、非平稳性及噪声背景较强等特点，为了有效提取故障特征，使用的一种共振稀疏分解（Resonance-based sparse signal decomposition，RSSD）与小波变换相结合的振动信号特征提取技术的相关仿真实验程序和轴承数据分解程序。其中，共振稀疏分解是基于品质因子可调小波变换与形态分量分析的一种新的信号分解方法，与常规的基于频带划分的信号分解方法不同，它依据信号各分量的振荡形态不同对信号进行分解。
同时还提供了可调谐 Q 因子小波变换 (TQWT)工具箱，TQWT 是类似于理性扩张小波变换（RADWT），但 TQWT 不要求伸缩因子是合理的。
同时也提供了MATLAB遗传算法工具箱Genetic Algorithm Toolbox的相关程序以及使用说明。
-In order to effectively extract the fault characteristics, a resonant sparse decomposition (RSSD) is used to compare the characteristics of the wavelet transform with the wavelet transform phase. In this paper, the resonant vibration signal of the rolling bearing is characterized by non-linearity, nonstationarity and strong noise background. Combined with the vibration signal feature extraction technology related to the simulation of experimental procedures and bearing data decomposition program. Platform: |
Size: 5875712 |
Author:聂凯 |
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Description: 遗传算法提供了求解非线性规划的通用框架，它不依赖于问题的具体领域。遗传算法的优点是将问题参数编码成染色体后进行优化， 而不针对参数本身， 从而不受函数约束条件的限制； 搜索过程从问题解的一个集合开始， 而不是单个个体， 具有隐含并行搜索特性， 可大大减少陷入局部最小的可能性。而且优化计算时算法不依赖于梯度信息，且不要求目标函数连续及可导，使其适于求解传统搜索方法难以解决的大规模、非线性组合优化问题。(Genetic algorithm provides a general framework for solving nonlinear programming, which does not depend on the specific problem domain. The advantage of genetic algorithm is that the problem parameters are encoded into chromosomes for optimization, rather than the parameters themselves. The search process starts from a set of problem solutions, rather than a single individual, and has the implicit parallel search feature, which can greatly reduce the possibility of falling into the local minimum. Moreover, the algorithm does not rely on gradient information and does not require the objective function to be continuous and differentiable, which makes it suitable for solving large-scale and nonlinear combinatorial optimization problems that are difficult to be solved by traditional search methods.) Platform: |
Size: 33792 |
Author:FZenjoys |
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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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Description: 用二进制遗传算法做特征选择，此算法效率高，选择的特征数目少。(The binary genetic algorithm is used for feature selection, which has high efficiency and few features.) Platform: |
Size: 3343360 |
Author:xiaohe1234 |
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Search - genetic algorithm feature matlab