Risk assessment and its visualization of power tower under typhoon disaster based on machine learning algorithms

• Main Authors: Hou, Hui, Yu, Shiwen, Wang, Hongbin, Huang, Yong, Wu, Hao, Xu, Yan, Li, Xianqiang, Geng, Hao
• Other Authors: School of Electrical and Electronic Engineering
• Format: Article
• Language: English
• Published: 2019
• Subjects: DRNTU::Engineering::Electrical and electronic engineering; Power Tower; Typhoon
• Online Access: https://hdl.handle.net/10356/106260; http://hdl.handle.net/10220/48903; http://dx.doi.org/10.3390/en12020205
• Institution: Nanyang Technological University

For power system disaster prevention and mitigation, risk assessment and visualization under typhoon disaster have important scientific significance and engineering value. However, current studies have problems such as incomplete factors, strong subjectivity, complicated calculations, and so on. The...