Study on the pre-warning system of public opinion based on PCA and PSO-SVM

DOI

10.2991/icmemtc-16.2016.131How to use a DOI?

Keywords

Index System; Principal Component Analysis; Support Vector Machine; Particle Swarm Optimization.

Abstract

In "Internet+" era, how to real-time monitoring and build effective pre-warning systems of the network public opinion crisis has become a required courses for government departments and enterprises. This paper sufficiently considers the development,changes in laws and characteristics of the network public o-pinion crisis, and establishes a pre-warning index system with 7 indexes of network public opinion. Because of the final index redundancy and the lack of data, building the public opinion of Pre-Warning model based on PCA and SVM, and using PSO to optimize the parameters of SVM. Experiment shows the pre-warning index system of network public opinion and the model of PCA-PSO-SVM is effective and feasible.

Copyright

© 2016, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Xiaohong Hao
AU  - Kaicheng Gu
AU  - Boyu Meng
PY  - 2016/04
DA  - 2016/04
TI  - Study on the pre-warning system of public opinion based on PCA and PSO-SVM
BT  - Proceedings of the 2016 3rd International Conference on Materials Engineering, Manufacturing Technology and Control
PB  - Atlantis Press
SP  - 661
EP  - 664
SN  - 2352-5401
UR  - https://doi.org/10.2991/icmemtc-16.2016.131
DO  - 10.2991/icmemtc-16.2016.131
ID  - Hao2016/04
ER  -