This thesis presents one of this techniques, an online version of the algorithm for training the support vector machine for regression and also how it has been extended in order to be more flexible for the hyper parameter estima- tion. Furthermore the algorithm has been compared with a batch ...
A prediction model of ion concentration based on online support vector regression is proposed for the characteristic of large delay in the process of detecting the metal ion concentration and the problem of model failure in the purification process of zinc hydrometallurgy. An old sample data is remo...
In this work, we propose a regression method to predict the popularity of an online video measured by its number of views. Our method uses Support Vector Regression with Gaussian Radial Basis Functions. We show that predicting popularity patterns with this approach provides more precise and more ...
In this work, Raman spectroscopy and a machine learning technique known as support vector regression (SVR) are used for building an online sensor to monitor the heterotrophic algal culture conditions in a computer-interfaced bench-scale microalgal bioreactor system, for the production of bio-oil. ...
在线鲁棒最小二乘支持向量机回归建模 Modeling method of online robust least-squares-support-vector regression 文档格式: .pdf 文档大小: 451.12K 文档页数: 6页 顶/踩数: 0/0 收藏人数: 0 评论次数: 0 文档热度: 文档分类: 幼儿/小学教育--教育管理 ...
Support vector regression (SVR) is an effective method for the predication of chaotic time-series, which is a fundamental topic of nonlinear dynamics. Through analyzing the possible variation of support vector sets after new samples are inserted to the t
2.3. Support Vector Regression Model Support vector classification (SVC) and support vector regression (SVR) are the two main categories for SVM. We established the SVR model for prediction, since we tend to get the growth rate of CHO with 7 medium supplements and to recognize the most importa...
Based on fuzzy clustering and multi-model support vector regression, a novel lithium-ion battery state of charge (SOC) estimating model for electric vehicl... X Hu,F Sun - International Conference on Intelligent Human-machine Systems & Cybernetics 被引量: 52发表: 2009年 加载更多来源...
Based on the assumption that neighbouring sensors have correlated measurements and that the instantiation of drift in a sensor is uncorrelated with other sensors, each sensor runs a support vector regression algorithm on its neigbourspsila corrected readings to obtain a predicted value for its ...
(2020) proposed a hybrid electric load forecasting model based on support vector regression, cuckoo search algorithm and variational mode decomposition. However, we know that many forecasting methods from different literatures are implemented offline. In fact, the good application of any kind of load ...