Cluster Computing

, Volume 21, Issue 1, pp 845–853 | Cite as

Prediction method of icing thickness of transmission line based on MEAO

  • Wei XiongEmail author
  • Hejin Yuan
  • Lang You


Transmission line icing is very important for safe operation of transmission network. Icing thickness of transmission line has characteristics including nonlinear growth, complicated influencing factors, long-term prediction and low accuracy. Based on intelligent prediction algorithms such as BP neutral network and support vector machine, the work proposed intelligent prediction method of icing thickness optimized by mind evolution algorithm. After modeling on basis of crucial factors of transmission line icing, we conducted simulation experiments of temperature, humidity and wire tension. Result shows that prediction model, with better performance than original intelligent method, can be used to more accurately predict icing thickness of transmission line.


Mind evolution algorithm optimization Icing thickness prediction of transmission line Correlation analysis Neural network Support vector machine 



This work was supported by the Fundamental Research Funds for the Central Universities (No. 2016MS151).


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Copyright information

© Springer Science+Business Media New York 2017

Authors and Affiliations

  1. 1.School of Control and Computer EngineeringNorth China Electric Power UniversityBaodingChina

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