Algorithm Research & Explore
|
421-425

Prediction method for IPTV user’s complaint based on LFOA-HSRVM algorithm

Liu Chao1
Chen Chunbing1
Wang Pan2
1. School of Electrical & Information Engineering, Jiangsu University, Zhenjiang Jiangsu 212003, China
2. School of Modern Posts, Nanjing University of Posts & Telecommunications, Nanjing 210003, China

Abstract

Aiming at the problems of numerous complaint factors and relatively poor fault samples of Internet protocol TV users, this paper proposed the LFOA-HSRVM algorithm as a prediction method for IPTV user's complaint combined with the outstanding sparsity of relevance vector machine. The method regarded fault prediction of IPTV user as a binary-classification problem with imbalanced data sets. The algorithm was based on the nuclear parameter optimization of RVM and hybrid sampling technology to overcome the problem that the decision boundary of the traditional RVM algorithm was biased to the minority class when dealing with imbalanced data sets. Compared with other algorithms, the experimental results show that the algorithm's performance of few classification and overall classification are improved greatly, and the effect of prediction is better.

Foundation Support

江苏省博士后基金资助项目(1402095C)
江苏大学高级人才科研启动基金资助项目(1291140025)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2019.12.0661
Publish at: Application Research of Computers Printed Article, Vol. 38, 2021 No. 2
Section: Algorithm Research & Explore
Pages: 421-425
Serial Number: 1001-3695(2021)02-017-0421-05

Publish History

[2021-02-05] Printed Article

Cite This Article

刘超, 陈春冰, 王攀. 基于LFOA-HSRVM的IPTV用户报障预测方法 [J]. 计算机应用研究, 2021, 38 (2): 421-425. (Liu Chao, Chen Chunbing, Wang Pan. Prediction method for IPTV user’s complaint based on LFOA-HSRVM algorithm [J]. Application Research of Computers, 2021, 38 (2): 421-425. )

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  • Application Research of Computers Monthly Journal
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Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

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