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2018 | OriginalPaper | Chapter

Power Network Vulnerability Detection Based on Improved Adaboost Algorithm

Authors : Wenwei Tao, Song Liu, Yang Su, Chao Hu

Published in: Cloud Computing and Security

Publisher: Springer International Publishing

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Abstract

The impact of the Internet on the power industry is increasing, the detection of power network vulnerability becomes more and more important. Traditional power network vulnerabilities detection methods are relatively labor-intensive and inefficient, so, the power network vulnerability detection algorithm based on improved Adaboost is proposed in this paper. It is a kind of machine learning algorithm, which select C4.5 decision tree as weak classifier to integrate a strong classifier. Compared with neural network, KNN and other methods, the proposed algorithm is more efficient in power network vulnerability detection.

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Title: Power Network Vulnerability Detection Based on Improved Adaboost Algorithm
Authors: Wenwei Tao
Song Liu
Yang Su
Chao Hu
Publisher: Springer International Publishing
Book: Cloud Computing and Security
Print ISBN: 978-3-030-00011-0

Electronic ISBN: 978-3-030-00012-7

Copyright Year: 2018
DOI: https://doi.org/10.1007/978-3-030-00012-7_58

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