Prediction of Line Fault Based on Optimized Decision Tree

DOI

10.2991/cmsa-18.2018.34How to use a DOI?

Keywords

mutual information; decision tree; line fault; correlation analysis

Abstract

Power line is the main equipment of transmission link, and its failure prediction will help to improve the safe operation level of the power grid and ensure the reliable electricity consumption of users. In this paper, the optimized decision tree algorithm is used to forecast fault line tripping. Firstly, correlation analysis algorithm of line run data attribute is being used to mining associate rules to build the analysis object. Secondly, mutual information is used to confirm the influence degree of various factors on the line tripping. Finally, based on the optimized decision tree algorithm to build the line fault prediction model, realize the early warning analysis of the line tripping. Through the implementation of the above methods, the active perception ability of the power grid is further enhanced to ensure the reliable operation of the power grid.

Copyright

© 2018, 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  - Jianping Yang
AU  - Jingxian Qi
AU  - Kang Ye
AU  - Youlin Hu
PY  - 2018/04
DA  - 2018/04
TI  - Prediction of Line Fault Based on Optimized Decision Tree
BT  - Proceedings of the 2018 International Conference on Computer Modeling, Simulation and Algorithm (CMSA 2018)
PB  - Atlantis Press
SP  - 146
EP  - 149
SN  - 1951-6851
UR  - https://doi.org/10.2991/cmsa-18.2018.34
DO  - 10.2991/cmsa-18.2018.34
ID  - Yang2018/04
ER  -