Journal of Systems Engineering and Electronics ›› 2010, Vol. 32 ›› Issue (10): 2136-2140.doi: 10.3969/j.issn.1001-506X.2010.10.26
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JING Xianyong1,XIAO Mingqing1,YU Wenbo2,ZHAO Xin1
Online:
Published:
Abstract:
A multi-steps forecast model possessing high precision based on procedure neural network (PNN) is established. Aiming at the complexity of training PNN, a new algorithm based on combining orthogonal function basis expansion and vector distance based immune algorithm (VD-IA) is proposed. The mathematic model of PNN that is expressed based on orthogonal trigonometric function basis is used to deduce the optimization model suitable to the VD-IA. An adaptive strategy is designed to obtain quick convergence process. The validity of the proposed method is vertified by Mackey-Glass chaotic sequence and is compared with both BP algorithm and improved particle swarm optimization (IPSO) algorithm. Simulation results show that the outstanding results can be obtained by using VD-IA, and the generalization performance of the IA-PNN is also outstanding.
JING Xianyong,XIAO Mingqing,YU Wenbo,ZHAO Xin. Application of improved immune algorithm in forecast procedure neural network[J]. Journal of Systems Engineering and Electronics, 2010, 32(10): 2136-2140.
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URL: https://www.sys-ele.com/EN/10.3969/j.issn.1001-506X.2010.10.26
https://www.sys-ele.com/EN/Y2010/V32/I10/2136