Research on Modeling of Pump Model Based on RBF Neural Network

Authors

Qinghui Wu, College of Engineering, Bohai University, Jinzhou 121013, China;
Qinghuan Shen, College of Engineering, Bohai University, Jinzhou 121013, China;
Xinjun Wang, College of Engineering, Bohai University, Jinzhou 121013, China;

Abstract

Abstract: On the basis of research on pump characteristics and pump model, a modeling method based on RBF neural network with K-means clustering algorithm was proposed. With k-means clustering algorithm the center vector and base width parameters, in which lie in the hidden layer, were optimized by input data sample. The weights between the hidden layer and the output layer were optimized by input-output data sample with least squares method. The neural network models of the pump characteristic and pump comprehensive model were separately trained and checked using the detected data. Its results suggest that reasonably choosing the number of hidden layer node and overlap coefficient, the trained neural network can substitute for the classic polynomial equations of the pump characteristics and the pump comprehensive model, and is with high accuracy.

Recommended Citation

Wu, Qinghui; Shen, Qinghuan; and Wang, Xinjun (2020) "Research on Modeling of Pump Model Based on RBF Neural Network," Journal of System Simulation: Vol. 28: Iss. 4, Article 5.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol28/iss4/5

First Page

800

Revised Date

2015-03-08

DOI Link

https://doi.org/

Last Page

805

CLC

S277.9;TU991

Recommended Citation

Wu Qinghui, Shen Qinghuan, Wang Xinjun. Research on Modeling of Pump Model Based on RBF Neural Network[J]. Journal of System Simulation, 2016, 28(4): 800-805.