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Improving the vector auto regression technique for time-series link prediction by using support vector machine

机译：使用支持向量机改进用于时间序列链路预测的矢量自助回归技术

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Jan Miles Co; Proceso Fernandez;
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1. Improving the vector auto regression technique for time-series link prediction by using support vector machine [J] . MATEC Web of Conferences . 2016,第2016期

机译：利用支持向量机改进向量自动回归技术进行时序链接预测
2. Permeability prediction using hybrid techniques of continuous restricted Boltzmann machine, particle swarm optimization and support vector regression [J] . Gu Yufeng, Bao Zhidong, Cui Guodong Journal of natural gas science and engineering . 2018,第期

机译：使用连续限制的Boltzmann机，粒子群优化和支持向量回归的渗透性预测
3. Prediction of Activity Cliffs Using Condensed Graphs of Reaction Representations, Descriptor Recombination, Support Vector Machine Classification, and Support Vector Regression [J] . Horvath Dragos, Marcou Gilles, Varnek Alexandre, Journal of chemical information and modeling . 2016,第9期

机译：使用反应表示，描述符重组，支持向量机分类和支持向量回归的浓缩图预测活动悬崖
4. A Comparative Study of Slope Failure Prediction Using Logistic Regression, Support Vector Machine and Least Square Support Vector Machine Models [C] . Lim Yi Zhou, Fam Pei Shan, Kunio Shimizu, National Symposium on Mathematical Sciences . 2017

机译：逻辑回归坡度故障预测的比较研究，支持向量机和最小二乘支持向量机模型
5. Support vector machines for regression and its application for prediction of machine degradation based on vibration signals. [D] . Lin, Hui. 2006

机译：支持向量机用于回归分析及其在基于振动信号的机械退化预测中的应用。
6. Improving model predictions for RNA interference activities that use support vector machine regression by combining and filtering features [O] . Andrew S Peek 2007

机译：通过组合和过滤特征使用支持向量机回归来改进RNA干扰活动的模型预测
7. Study Of E-Smooth Support Vector Regression And Comparison With E- Support Vector Regression And Potential Support Vector Machines For Prediction For The Antitubercular Activity Of Oxazolines And Oxazoles Derivatives [O] . Doreswamy, Vastrad, Chanabasayya M. 2013

机译：E-smooth支持向量回归的研究及与E-的比较支持向量回归和潜在支持向量机预测恶唑啉和恶唑类的抗结核活性衍生品
8. Linking Learning Strategies and Performance for Support Vector Machines [R] . Howse, J., Hush, D., Scovel, C. 2002

机译：为支持向量机链接学习策略和性能

Improving the vector auto regression technique for time-series link prediction by using support vector machine

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