Research on line overload identification of power system based on improved neural network algorithm-Reference-Cited by-同舟云学术

Research on line overload identification of power system based on improved neural network algorithm

Published:2020-07-20 Issue:24 Volume:32 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Yang Lin¹^ORCID,Luo Zhiming²,Lin Wangqing¹,Li Shaozi¹

Affiliation:

1. Department of Artificial Intelligence Xiamen University Xiamen PR China

2. Post‐doctoral Mobile Station of Information and Communication Engineering Xiamen University Xiamen PR China

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.5933

Reference24 articles.

1. HVDC transmission line protection based on single‐ended transient current using multiband energy;Xu X;Power Sys Protect Control,2016

2. Identification of fault area in power system based on colored selfmodifying Petri nets;Min X;Power Sys Protect Control,2016

3. Differential Privacy Techniques for Cyber Physical Systems: A Survey

4. A local outlier factor fault identification algorithm based on the co‐simulation between cyber and power system for distribution network;Zhang Z;Automat Electr Power Sys,2016

5. High performance computing for cyber physical social systems by using evolutionary multi‐objective optimization algorithm;Wang GG;IEEE Trans Emerg Top Comput,2020

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Comparison of Short-Term Electrical Load Forecasting Models using Datasets from The Building Automation System in The Department of Electrical Engineering ITN;2023 IEEE International Conference on Communication, Networks and Satellite (COMNETSAT);2023-11-23

2. Application of Improved Algorithm of BP Neural Network;Advanced Intelligent Technologies for Industry;2022