Identification of Flow Ｒegimes Based on Adaptive Learning and Additional Momentum BP Neural Network for Electrical Capacitance Tomography
Traditional BP neural network is a typical mehtod to solve ECT system of flow pattern identification. It is applied to the simple problems in industrial applications，but there are many defects in solving complex industrial problems. In this paper based on the analysis of deficiency of BP neural ne...
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| Main Authors: | , , , |
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| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2018-02-01
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| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1488 |
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| Summary: | Traditional BP neural network is a typical mehtod to solve ECT system of flow pattern identification.
It is applied to the simple problems in industrial applications，but there are many defects in solving complex
industrial problems. In this paper based on the analysis of deficiency of BP neural network，for reducing the error
oscillation，the adaptive learning rate adjustment factor and the additional momentum is introduced. In this method，
the electrical capacitance values are input to train a network to identify the flow patterns. The simulation results
show the algorithm not only inherits the advantages of traditional BP neural network，but also improve slow
convergence and solve being prone to fall into local minimum problems in flow pattern identification of ECT system |
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| ISSN: | 1007-2683 |