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author:

Lin, Z.-S. (Lin, Z.-S..) [1] | Zhang, Q.-S. (Zhang, Q.-S..) [2] | Liu, H. (Liu, H..) [3]

Indexed by:

Scopus

Abstract:

There are many methods to improve the accuracy of GM(1,1) model and the Swarm intelligent algorithms can be used to optimize the development coefficient and grey action quantity of GM(1,1) model effectively. In this paper, an optimization GM(1,1) model about identifying the parameters is proposed, which takes the minimum of the average relative error as the objective function. Moreover, an improved artificial fish swarm algorithm is designed to solve the optimization model. The simulation results show that the proposed method may enhance the precision of GM(1,1) model, which has a better performance than Particle Swarm Optimization. © 2011 IEEE.

Keyword:

artificial fish swarm algorithm; GM(1,1) model; parameter optimization

Community:

  • [ 1 ] [Lin, Z.-S.]Department of Engineering Management, Fujian University of Technology, Fuzhou, China
  • [ 2 ] [Zhang, Q.-S.]School of Management, Fuzhou University, Fuzhou, China
  • [ 3 ] [Liu, H.]School of Economics and Management, Southeast University, Nanjing, China

Reprint 's Address:

  • [Lin, Z.-S.]Department of Engineering Management, Fujian University of Technology, Fuzhou, China

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Source :

Proceedings of 2011 IEEE International Conference on Grey Systems and Intelligent Services, GSIS'11 - Joint with the 15th WOSC International Congress on Cybernetics and Systems

Year: 2011

Page: 266-270

Language: English

Cited Count:

WoS CC Cited Count:

SCOPUS Cited Count: 3

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 1

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