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/).
Cite this article
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 -