Self-Training Enabled Efficient Classification Algorithm: An Application to Charging Pile Risk Assessment-Reference-Cited by-同舟云学术

Self-Training Enabled Efficient Classification Algorithm: An Application to Charging Pile Risk Assessment

Published:2022 Issue: Volume:10 Page:86953-86961
ISSN:2169-3536
Container-title:IEEE Access
language:
Short-container-title:IEEE Access

Author:

Wang Wen¹,Peng Xiaofeng¹,Yang Ye¹,Xiao Chun²,Yang Shuai²,Wang Mingcai¹,Wang Lingfei¹,Wang Yanling³,Li Lin³^ORCID,Chang Xiaolin³^ORCID

Affiliation:

1. State Grid Electric Vehicle Service Company Ltd, Beijing, China

2. State Grid Shanxi Marketing Service Center, Taiyuan, China

3. Beijing Key Laboratory of Security and Privacy in Intelligent Transportation, Beijing Jiaotong University, Beijing, China

Funder

State Grid Technology Project “Research on Interaction between Large-Scale Electric Vehicles and Power Grid and Charging Safety Protection Technology” from State Grid Corporation of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Link

http://xplorestaging.ieee.org/ielx7/6287639/9668973/09858055.pdf?arnumber=9858055

Reference24 articles.

1. Do you know your customer? Bank risk assessment based on machine learning

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4. Supervised machine learning: A review of classification techniquesm;kotsiantis;Emerg Artif Intell Appl Comput Eng,2007

5. Classification and regression trees

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