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csmmm
Custom Internet Search Bar for MATLAB
- 2010-12-16 20:39:09下载
- 积分:1
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GridResMan
RESOURCES MANAGEMENT IN GRID COMPUTING
- 2010-11-25 04:20:29下载
- 积分:1
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matlab_neat
说明: 这个是关于neural fuzzy 算法的工具箱, 有例子程序, 请您用winzip解压缩(is on the neural fuzzy algorithm toolbox, there are examples of procedures, please use winzip decompress)
- 2005-12-07 12:43:34下载
- 积分:1
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matlab_cyclicstationary_toolbox
对循环平稳信号进行处理的工具箱,适用MATLAB。()
- 2007-09-01 10:04:27下载
- 积分:1
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ICA(Matlab)
IEEE文章,带ICA算法源码,很好的参考,给大家分享一下(ICA matlab)
- 2010-05-30 21:58:15下载
- 积分:1
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dbf2800df370
包含MVC,GMV等的几种控制系统性能评估算法。还不错,分享一下(Generalized minimum variance control)
- 2013-12-21 22:52:00下载
- 积分:1
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SVM_Matlab_Sharp2
implementation of support vector machine
- 2013-11-30 12:51:32下载
- 积分:1
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genetic-fuzzy-(ga_fuzzy)
genetic fuzzy (ga_fuzzy) pid gain optimal
- 2013-12-09 07:41:58下载
- 积分:1
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counter_xr0yqc
无线信道OWzQYJ模型MATLAB仿真程序,实现了SrQGdSB技术下多参数的模拟,最接近物理信道,信道逼近参数接近最小二乘OWzQYJ算法。
(Radio channelOWzQYJ model MATLAB simulation program, to achieve a multi-parameter simulation SrQGdSB technology, the closest physical channel, the channel parameters close to the least square approximation algorithm OWzQYJ
)
- 2015-12-23 09:05:56下载
- 积分:1
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优秀论文及配套源码 SVM Short-term-Load-Forecasting
优秀论文及配套源码。首先阐述了负荷预测的应用研究现状,概括了负荷预测的特点及其影响因素,归纳了短期负荷预测的常用方法,并分析了各种方法的优劣;接着介绍了作为支持向量机(SVM)理论基础的统计学习理论和SVM的原理,推导了SVM回归模型;本文采用最小二乘支持向量机(LSSVM)模型,根据浙江台州某地区的历史负荷数据和气象数据,分析影响预测的各种因素,总结了负荷变化的规律性,对历史负荷数据中的“异常数据”进行修正,对负荷预测中要考虑的相关因素进行了归一化处理。LSSVM中的两个参数对模型有很大影响,而目前依然是基于经验的办法解决。对此,本文采用粒子群优化算法对模型参数进行寻优,以测试集误差作为判决依据,实现模型参数的优化选择,使得预测精度有所提高。实际算例表明,本文的预测方法收敛性好、有较高的预测精度和较快的训练速度。(first expounds the recent application research of load forecasting, summarized the characteristics of load forecasting and influencing factors, summed up common methods of short-term load forecasting, and analyzed the advantages and disadvantages of each method then introduced statistical learning theory and the principle of SVM as the basis of support vector machine (SVM ) theory, SVM regression model is derived this paper adopted least squares support vector machine (LSSVM) model, according to the historical load data and meteorological data of a certain area of Zhejiang Taizhou, Analysised the various factors affecting the forecast, summed up the regularity of load change , amended "outliers" in the historical load data,the load forecasting factors to be considered were normalized. The two parameters of LSSVM have a significant impact on the model, but it is still soluted based on the experience currently. So, this paper adopted particle swarm optimization algorithm to optimized )
- 2021-04-01 17:09:08下载
- 积分:1