Predicting number of online users by ε-SVR
Received date: 2015-11-30
Online published: 2016-02-29
顾纯栋 . 基于ε-SVR的用户视听在线人数预测[J]. 上海大学学报(自然科学版), 2016 , 22(1) : 97 -104 . DOI: 10.3969/j.issn.1007-2861.2015.05.001
Predicting the number of online audio-visual users can provide valuable information to help manufacturers get more profits. Based on time series analysis, support vector regression is used to make accurate prediction with adjusted feature. The time series is first modeled and predicted, a linear regression model used to make further improvement, and then, by combining time and real-life characteristics, adding a new feature. Samples of the new feature are trained with support vector regression. Optimal parameters of the radial basis function are sought using the social cognitive optimization. A good prediction result can be obtained using the proposed method.
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