Modeling for A Complicated Industrial Object Based on Recurrent Neural Network

Wei Jianping; Li Huade; Yu Datai; Feng Yang

doi:10.13374/j.issn1001-053x.1999.04.025

Volume 21 Issue 4

Aug. 2021

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Article Navigation > Chinese Journal of Engineering > 1999 > 21(4): 406-408

Wei Jianping, Li Huade, Yu Datai, Feng Yang. Modeling for A Complicated Industrial Object Based on Recurrent Neural Network[J]. Chinese Journal of Engineering, 1999, 21(4): 406-408. doi: 10.13374/j.issn1001-053x.1999.04.025

Citation:

Wei Jianping, Li Huade, Yu Datai, Feng Yang. Modeling for A Complicated Industrial Object Based on Recurrent Neural Network[J]. Chinese Journal of Engineering, 1999, 21(4): 406-408. doi: 10.13374/j.issn1001-053x.1999.04.025

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Modeling for A Complicated Industrial Object Based on Recurrent Neural Network

doi: 10.13374/j.issn1001-053x.1999.04.025

Information Engineering School, UST Beijing, Beijing 100083, China

Received Date: 1998-12-03
Available Online: 2021-08-27

Abstract

Abstract

The architecture and algorithm of a kind of dynamical neural network, Elman recurrent neural network (RNN)were dicussed. Based on this network, an approach of modeling for nonlinear time-varying industrial object, direct current arc, was proposed. Compared with other modeling method for the object, the model based on RNN is proved to have better performance.
- recurrent neural network,
- modeling,
- industrial object