Description: 用于非线性系统预测滤波的经典算法，由最小支持向量机算法创始人亲自编写。-Prediction filter for nonlinear systems of the classical algorithm, from the smallest support vector machine algorithm for the preparation of the founder himself. Platform: |
Size: 995328 |
Author:123456 |
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Description: 支持向量机的分类和回归算法,可用于模式识别和预测-Support vector machine classification and regression algorithms can be used for pattern recognition and prediction Platform: |
Size: 75776 |
Author:费小东 |
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Description: 一种基于matlab的支持向量机小例子，用于预测，LS-A matlab-based support vector machine small example for the prediction, LS Platform: |
Size: 224256 |
Author:Misa |
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Description: 支持向量机工具箱，可进行分类，预测等，实现了四种支持向量机工具箱的分类与回归算法，有实例-Support Vector Machine Toolbox, it can conduct classification, prediction and so on, implementation of the four support vector machine toolbox classification and regression algorithm, has examples of Platform: |
Size: 2946048 |
Author: 罗洁思 |
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Description: 一类支持向量机，用于分类和预测，里面代码使用matlab编程-One-Class Support Vector Machine for classification and prediction, which code to use matlab programming Platform: |
Size: 1024 |
Author:赵桓 |
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Description: 这是对于工业过程中连续搅拌釜反应器用支持向量机建模的实例。预测效果很好。-This is for the industrial process of continuous stirred tank reaction used in support vector machine modeling examples. Very good prediction. Platform: |
Size: 378880 |
Author:zhajuan |
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Description: 支持向量机的源代码，它的用途非常的广泛，比如在预测-Support vector machine' s source code, its use is very widespread, such as prediction, etc. Platform: |
Size: 83968 |
Author:chenkai |
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Description: 支持向量机非线性回归通用MATLAB源码本源码可以用于线性回归、非线性回归、非线性函数拟合、数据建模、预测、分类等多种应用场合-Universal non-linear regression support vector machine MATLAB source code of this source can be used for linear regression, nonlinear regression, nonlinear function approximation, data modeling, prediction, classification and other applications Platform: |
Size: 7168 |
Author:fangcao |
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Description: 针对基于GPS／GIS的浮动车数据特点，总结其中无效的数据类型，并给出数据有效处理的方法。以支持向量机原理、交通状态预测方法为基础，分析了常用支持向量回归机、核函数及模型参数的性能，以及各核函数及模型参数对支持向量机性能的影响及作用。针对路段平均速度预测中的小样本、非线性、高维回归等特点，将支持向量回归机方法引入基于浮动车数据的路段车辆速度预测，构建了路段平均速度短时预测模型。并以杭州市某路段的实际数据为例，详细阐述了支持向量回归机预测模型的具体建模和求解过程。运用LibSVM2．84软件包，进行预测模型的参数选择、样本训练以及预测求解，并通过预测结果的对比分析，验证了预测模型的可用性和有效性。-Characteristics of the GPS/GIS-based floating car data, summary of which types of invalid data, and gives the effective data processing method. Support vector machine, the traffic state prediction method based on analysis of commonly used support vector regression machines, nuclear function and performance of the model parameters, as well as the kernel function and model parameters on the performance of SVM and effect. Small sample, nonlinear, high dimensional regression for the prediction of average speed characteristics, the support vector regression machine to the introduction of prediction based on floating car data section of the speed of vehicles, build a short-term forecasting model of average speed. In Hangzhou section of the actual data, for example, elaborated on the specific modeling and solving process of the support vector machine for regression prediction model. Use LibSVM2.84 package forecast model parameter selection, sample training, and forecasting solution, and verif Platform: |
Size: 2207744 |
Author:tangshx |
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Description: Location prediction is a special case of spatial data mining
classification. For instance, in the public safety domain,
it may be interesting to predict location(s) of crime
hot spots. In this study, we present Support Vector Machine
(SVM) based approach to predict the location as alternative
to existing modeling approaches. SVM forms the new generation
of machine learning techniques used to find optimal
separability between classes within datasets. Experiments
on two different spatial datasets show that SVMs gives reasonable
results. Platform: |
Size: 197632 |
Author:ahmed |
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Description: Crime hot-spot location prediction is important for public safety. The output from the prediction
can provide useful information to improve the activities aimed at detecting and preventing
safety and security problems. Location prediction is a special case of spatial data mining classification.
For instance, in the public safety domain, it may be interesting to predict location(s) of
crime hot spots. In this study, we present a support vector machine (SVM)-based approach to predict
the location as an alternative to existing modeling approaches. Platform: |
Size: 453632 |
Author:ahmed |
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Description: 针对风电场短期风速的预测提出一种基于小波变换的组合预测方法。首先利用Mallat 算法对短期风速时间序列进行db3 小波三层分解与重构，得到短期风速时间序列的近似分量和细节分量。针对近似分量和细节分量的不同特性，对近似分量利用粒子群算法优化的最小二乘支持向量机进行预测，对细节分量利用自回归求和滑动平均模型进行预测。最后各预测模型预测值组合叠加得到最终的短期风速预测值。仿真结果表明该方法具有较高的预测准确度。-In order to improve short-term wind speed prediction accuracy of wind farms，a combined prediction method based on the wavelet transform is proposed. Firstly，the db3 wavelet is used for three-layer decomposition and reconstruction for short-term wind speed time series through Mallat algorithm. The approximation components and the detail components of the short-term wind speed are then obtained. Next，according to the different characteristics of these components，the least square support vector machine optimized
by particle swarm algorithm and the autoregressive integrated moving average model are adopted as the predictivemodels for the approximate components and the detail components respectively. Then，the final predictive value of the short-term wind speed is obtained by the combination of the two components. The simulation results indicate that higher accuracy can be obtained in this prediction method. Platform: |
Size: 289792 |
Author:kiel |
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Search - support vector machine for prediction