Telecommunications Science ›› 2020, Vol. 36 ›› Issue (3): 27-33.doi: 10.11959/j.issn.1000-0801.2020068

• Topic:Industrial Internet Platform and Security • Previous Articles     Next Articles

Improved fish swarm algorithm based on chaos and its application in abnormal detection of industrial control network

Yaping WU1,2,Hongzhao DONG1,Yingying LIN1,Jing LIU2   

  1. 1 College of Mechanical Engineering,Zhejiang University of Technology,Hangzhou 310032,China
    2 Mechanical and Electrical Engineering College,Shaoxing University,Shaoxing 312000,China
  • Revised:2020-03-13 Online:2020-03-20 Published:2020-03-26
  • Supported by:
    The National Natural Science Foundation of China(61773347);The Education Department Foundation of Zhejiang Province of China(LY17F030017)

Abstract:

Artificial fish swarm algorithm as a new type of bionic swarm intelligence optimization algorithm has been successfully used in a variety of optimization problems and practical engineering field,but when faced with the complex optimization problems,especially the multiple extreme value of peak and multimodal function optimization problems,due to the objective function has many local minima,inevitably there are defects such as premature and slow convergence speed.The random and ergodic theory was introduced into the basic artificial fish swarm algorithm,and an improved algorithm was constructed to make artificial fish swarm search avoid possible local extremum.The effectiveness of the algorithm was validated in the simulation application in industrial control network anomaly detection.Compared with the basic artificial fish school algorithm,the chaos improved artificial fish swarm algorithm can effectively avoid the long-term search of the algorithm near the local extreme value.The algorithm has better performance in terms of global convergence and the search efficiency is more prominent.

Key words: chaos, Logistic map, artificial fish swarm algorithm, optimization

CLC Number: 

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