搜索资源列表
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4下载：
用粒子群优化算法进行特征选择和SVM参数优化-Using Particle Swarm Optimization algorithm of feature selection and SVM parameter optimization
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基于扩展记忆的粒子群优化算法（Particle Swarm Optimization based on memory）-This paper combines SVM with improved PSO (Particle Swarm Optimization with Extended Memory, PSOEM) and then builds PSOEM-SVM forecasting model. The PSOEM searches the solution space intelli
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SVM神经网络中的参数优化---提升分类器性能-SVM neural network parameter optimization--- to enhance the performance of the classifier
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SVM神经网络中的参数优化---提升分类器性能,模型精度较高-SVM neural network classifier parameter optimization--- to enhance performance, high accuracy of the model
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svm参数优化方法，网格算法，可修改迭代次数等参数-svm parameter optimization method, the mesh algorithms can modify parameters such as the number of iterations
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利用网格搜索法对支持向量机的参数寻优的过程，通过matlab实现-Grid search method to use SVM parameter optimization process to achieve through matlab
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Matlab使用pso进行svm参数优化寻优-Matlab were svm parameter optimization using pso optimization
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Matlab使用pso进行svm参数优化寻优-Matlab were svm parameter optimization using pso optimization
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基于遗传算法的支持向量机算法，程序内可实现遗传算法参数寻优，并对输入数据分类输出-SVM based on genetic algorithms, genetic algorithms can be realized within the program parameter optimization, output and input data classification
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支持向量机的源代码，可以实现分类和回归分析。-ctions on Intelligent Systems and Technology
ABSTRACT LIBSVM is a library for Support Vector Machines (SVMs). We have been actively developing this package since the year 2000. The goal is to help users to easily apply SVM t
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包含优化类的几个简单示例程序，imRwnmw参数DC-DC部分采用定功率单环控制，本科毕设要求参见标准测试模型，在MATLAB中求图像纹理特征，OWpTJFr条件有信道编码，调制，信道估计等，包括最小二乘法、SVM、神经网络、1_k近邻法。- Optimization class contains several simple sample programs, imRwnmw parameter DC-DC power single-part set-loop control, Undergr
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SVM的参数优化——如何更好的提升分类器的性能-SVM parameter optimization: how to better improve the performance of the classifie
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和声搜索算法的，根据最新文献选用SVM参数优化，智能优化算法范例。-Harmony search algorithm, according to the latest literature selected SVM parameter optimization, intelligent optimization algorithm examples.
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该程序是基于粒子群算法优化支持向量机中的正则化参数C和核函数参数K的算法，实现了对电力负荷的短期预测，预测效果较好，可根据自己要求进行更改。-The algorithm is based on particle swarm optimization algorithm to optimize regularization parameter C and kernel function parameter K in support vector machine. It realizes the s
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基于粒子群（pso）的参数寻优，可以做BP和svm的参数寻优。-Based on Particle Swarm (pso) parameter optimization, BP and svm you can do the parameter optimization.
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将改进的粒子群算法和GA与SVM相结合，通过参数寻优构建新模型完成对空气质量指数的预测(The improved particle swarm optimization and genetic algorithm are combined with SVM. The prediction of air quality index (AQI) is completed by constructing a new model by parameter optimization.)
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SVM神经网络中的参数优化---如何更好的提升分类器的性能(Parameter Optimization in SVM Neural Network--How to Improve the Performance of Classifie)
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