Aero-engine arguments selection based on wavelet network mean impact value

被引：0
作者：
Cui, Zhi-Quan [1 ]
Fu, Xu-Yun [2 ]
Zhong, Shi-Sheng [2 ]
Wang, Ti-Chun [3 ]
机构：
[1] Department of Automotive Engineering, Harbin Institute of Technology at Weihai
[2] Department of Naval Architecture, Harbin Institute of Technology at Weihai
[3] Department of Mechanical and Electrical Engineering, Nanjing University of Aeronautics and Astronautics
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2013年 / 19卷 / 12期
关键词：
Aero-engine; Arguments selection; Mean impact value; Wavelet network;
D O I：
10.13196/j.cims.2013.12.cuizhiquan.3062.6.20131217
中图分类号：
学科分类号：
摘要：
To achieve the non-linear variables selection rapidly and accurately, the engine arguments parameters selection method for wavelet neural network's Mean Impact Value(MIV) was proposed based on the ideological of MIV and the advantages such as learning ability, fast convergence with adaptive and fault tolerance of wavelet neural network. According to the relationship characteristics of the engine parameters, the continuous multi-parameter approximation wavelet network model was established, and the learning algorithm was given. Simulation results showed that the proposed method could achieve complex nonlinear variable selection and have higher accuracy and faster features by comparing to other non-linear variable selection method.
引用
收藏
页码：3062 / 3067
页数：5
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