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[AI-NN-PR] OnlineSVRCCode DL : 0: 在线支持向量机C＋＋程序,程序中包含了应用的例子-Online Support Vector Machine C program, the program contains examples of applications
Date : 2025-12-25 Size : 555kb User : 张文斌
[AI-NN-PR] svr DL : 0: svr(support vector regression),即支持向量回归，是人工神经网络的一种学习算法。可用于数据预测等。
Date : 2025-12-25 Size : 1kb User : 王珏
[AI-NN-PR] MYGASVM DL : 0: simple GASVM for LS-SVM
Date : 2025-12-25 Size : 224kb User : vim
[AI-NN-PR] SVM_Toolbox DL : 0: Matlab源代码，包括支持向量机分类算法（SVC_C，SVC_Nu）,回归算法（SVR_Epsilon，SVR_Nu）,以及One-Class算法。-Matlab source code, including support vector machine classification algorithm (SVC_C, SVC_Nu), regression algorithm (SVR_Epsilon, SVR_Nu), as well as the One-Class algorithm.
Date : 2025-12-25 Size : 223kb User : 李志
[AI-NN-PR] smo1forsvr DL : 0: 一种快速的SVM算法。初学者有用。MATLAB程序。-A Fast SVM algorithm. Useful for beginners. MATLAB program.
Date : 2025-12-25 Size : 2kb User : kaku
[AI-NN-PR] libsvm-2.85-dense DL : 0: LIBSVM源码。LIBSVM 是台湾大学林智仁(Chih-Jen Lin)博士等开发设计的一个操作简单、易于使用、快速有效的通用SVM 软件包，可以解决分类问题（包括C- SVC、 n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ）等问题，提供了线性、多项式、径向基和S形函数四种常用的核函数供选择，可以有效地解决多类问题、交叉验证选择参数、对不平衡样本加权、多类问题的概率估计等。-LIBSVM source. LIBSVM is林智仁Taiwan University (Chih-Jen Lin) Dr. develop design a simple, easy to use, fast and effective generic SVM software package, can solve the classification problems (including the C-SVC, n- SVC), regression ( including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM) and so on, provides a linear, polynomial, radial basis function and the S-shaped kernel function of four commonly used for selection, can effectively to solve a wide range of issues, cross-validation to choose the parameters of the imbalance in the weighted sample, multi-category probability estimation.
Date : 2025-12-25 Size : 24kb User : 刘铁军
[AI-NN-PR] pso-svm DL : 1: 利用PSO优化SVM，利用分组式训练方法提高算法速度-PSO to optimize the use of SVM, the use of packet-style training methods improve algorithm speed
Date : 2025-12-25 Size : 109kb User : zhangqing
[AI-NN-PR] LS-SVMlab1.5 DL : 0: SVM 软件包，可以解决分类问题（包括C- SVC、n - SVC ）、回归问题（包括e - SVR、n - SVR ）以及分布估计（one-class-SVM ）等问题-SVM software package can solve the classification problems (including the C-SVC, n- SVC), regression (including e- SVR, n- SVR) as well as the distribution of estimates (one-class-SVM) and other issues
Date : 2025-12-25 Size : 32kb User : hanzeyu
[AI-NN-PR] Vsvm3.0AndCode DL : 0: svm算法兼容libsvm格式和各种算法，包括多目标回归 -svm svr svc and so on
Date : 2025-12-25 Size : 1.11mb User : pww
[AI-NN-PR] PS0-SVR DL : 0: ：针对发酵过程中生物参数难以实时在线测量的问题，建立了用于生物参数状态预估的支持向量机软测量模型。考虑到该支持向量回归(SVR)模型的复杂性和冷化特征取决于其三个参数，c，能否取到最优值，采用粒子群优化(PSO)算法实现对参数，c，的同时寻优。在此基础上，以饲料用．甘露聚糖酶为对象，建立了基于PSO—SVR的发酵过程产物浓度状态预估模型。发酵罐控制结果表明：该模型具有很好的学习精度和泛化能力，可实现对．甘露聚糖酶产物浓度的实时在线预估。-In view of the hardship to get real—time and on—line biological parameters in fermentation process，a soft sensor model based on support vector machines is established for estimating the bio— logical parameters．The complexity and generalization performance of the support vector regression (SVR)model depend on a good setting of the three parameters ，c，．An algorithm called parti— cle swarm optimization(PSO)is applied to optimize the three parameters synchronously．Based on the proposed method，a PSO—SVR model is developed to estimate the products concentration of beta— mannanase for feedstuf．The control results of fermenter show that the state estimation model based on PSO·-SVR has good learn ing accuracy and generalization perform ance SO as to obtain the real·-time and on—line estimation for products concentration of beta—mannanase．
Date : 2025-12-25 Size : 226kb User : 11
[AI-NN-PR] TimeSeriesPredictionUsingSupportVectorRegressionNe DL : 0: 为了选择神经网络的最好结构以及增强模型的推广能力，提出一种自适应支持向量回归神经网络(SVR—NN)。SVR—NN 用支持向量回归(SVR)方法获得网络的初始结构和权值，白适应地生成网络隐层结点，然后用基于退火过程的鲁棒学习算法更新网络结点疹教和权主。 SVR—NN有很好的收敛性和鲁棒性，能抑制由于数据异常和参数选择不当所导致的“过拟合，’现象。将SVR—NN 应用到时间序列预测上。结果表明，SVR．NN预测模型能精确地预测混沌时间序列，具有很好的理论和应用价值。-Abstract：To select the‘best’structure of the neural networks and enhance the generalization ability of models．a support vector regression neural networks fSVR-NN)was proposed．Firstly，support vector regression approach was applied to determine initial structure and initial weights of SVR．NN SO that the number of hidden layer nodes can be constructed adaptively based on support vectors．Furthermore，an annealing robust learning algorithm was further presented to fine tune the hidden node parameters and weights of SVR一ⅣM The adaptive SVR．NN has faSt convergence speed and robust capability．and it can also suppress the ‘orerfitting’phenomena when the train data ncludes outliers．The adaptive SVR．NN was then applied to time series prediction．Experimental results show that the adaptive SVR．ⅣⅣ can accurately predict chaotic time series，and it iS valuable in both theory and application aspects．
Date : 2025-12-25 Size : 309kb User : 11
[AI-NN-PR] ForecastingpopIllafionbasedOnsupportvectorintellig DL : 0: 要建立一个有效的支持向量回归(SVR)模型，支持向量回归的3个参数c，y，占丛须预先设定。提出一种新型的遗传算法一智能遗传算法(IGA)对支持向量回归进行参数调节，以达到寻找最优参数的目的，然后和支持向量回归结合得到一种新的 IGASVR模型，并应用于城市人口预测。最后，将提出的方法与标准SVR模型和BP神经网络模型进行比较，所得结果表明，该模型训练速度快，并且有较高预测精度，是一种有效的人口预测方法。-To build an effective SVR model，SVR’8 parameters must be set carefully．This study proposes a novel approach， known ag IGASVR。which searches for SVR’s optimal parameters using intelligent genetic algorithms，and then adopts the optimal parameters to construct the SVR models．Finally we apply IGASVR tO forecast population．The experimental results demonstrates that IGASVR are better than standard SVR and BP neural-network．IGASVR model is an effective approach which has faster speed of training and higher precision．
Date : 2025-12-25 Size : 364kb User : 11
[AI-NN-PR] svm DL : 0: 统计学习理论中提出的支撑向量机回归(SVR)遵循了结构风险最小化原则,从而避免了一味追求经验风险最小化带来的弊端-Statistical learning theory proposed by the support vector machine regression (SVR) to follow the structural risk minimization principle, thus avoiding the blind pursuit of Empirical Risk Minimization the evils of
Date : 2025-12-25 Size : 3kb User : han fei
[AI-NN-PR] SVR DL : 0: SVR 支持向量回归机，这是SVM的一种拓展类型，可以有效的完成非线性拟合-SVR support vector regression, which is an expanding type of SVM, can effectively complete the nonlinear fitting
Date : 2025-12-25 Size : 3.21mb User : yuanxuegeng
[AI-NN-PR] IRWLS-SVR-code DL : 1: IRWLS-SVR即基于迭代加权最小二乘的支持向量机回归-IRWLS-SVR，Support vectors based on iteratively reweighted least squares
Date : 2025-12-25 Size : 9kb User : 王党
[AI-NN-PR] svr DL : 0: svm回归用来预测回归的参数没有调结果不好(svm bbbdhua dsjffb ervg dr fer)
Date : 2025-12-25 Size : 1kb User : ligialigia
[AI-NN-PR] farutoUltimateVersion2[1].0 DL : 0: SVR工具箱，可以用来参数预测，还可以应用于优化设计中(SVR toolbox, used for the prediction and optization)
Date : 2025-12-25 Size : 330kb User : great_mk
[AI-NN-PR] pso-svr代码 DL : 0: 基于粒子群优化的向量回归预测分析 matlab代码(Support vector regression code with pso)
Date : 2025-12-25 Size : 1kb User : 1adams
[AI-NN-PR] 交叉验证及svr DL : 0: 交叉验证及带例子的支持向量机回归代码，修改可用。(Cross validation and support vector machine regression code with examples can be modified.)
Date : 2025-12-25 Size : 20kb User : vein
[AI-NN-PR] python DL : 0: 该代码基于Python3,利用机器学习中支持向量机回归算法（SVR）实现对数据的拟合以及预测，可以通过调试C值和gamma值达到不同的拟合程度，具有较大的实际意义，并且该代码本人亲自调式运用，适合广大学习者使用。(This code is based on Python 3. It uses support vector machine regression algorithm (SVR) in machine learning to fit and predict the data. It can achieve different fitting degree by debugging C value and gamma value. It has great practical significance. Moreover, the code itself can be used in a way that is suitable for the majority of learners.)
Date : 2025-12-25 Size : 1kb User : 帅毛毛

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