Journal of Dalian Maritime University >
2021 , Vol. 47 >Issue 1: 101 - 110
DOI: https://doi.org/10.16411/j.cnki.issn1006-7736.2021.01.012
Prediction of compressor flow characteristics based on neural network optimized by ring topology adaptive differential evolution algorithm
Received date: 2020-12-30
Revised date: 2021-02-21
Online published: 2021-02-21
In order to improve the simulation accuracy of diesel engine in marine engine room simulator under non rated conditions, a hybrid method based on limited data was proposed to predict the compressor flow characteristics under multiple conditions. In this method, a ring topology differential evolution (DE) algorithm was used to optimize the parameters of the three-layer feedforward neural network (FNN), and the flow characteristic curve of the compressor was predicted by using the limited flow characteristic data under given conditions. A FNN was used to fit the nonlinear mapping of compressor flow characteristics, and the DE algorithm was used to adjust the important parameters, such as connection weight, connection bias and connection switch. The simulation results show that the method based on limited data can better fit the flow characteristics of marine compressor, and the adaptive differential evolution algorithm with ring topology is effective to optimize and adjust the important parameters of neural network. The hybrid method proposed in this paper has better generalization ability and search accuracy, which can be used as an effective means to deal with similar prediction problems.
JIANG Rui-zheng , ZHANG Jun-dong , FENG Jin-hong , SHEN Hao-sheng , WANG Chuan . Prediction of compressor flow characteristics based on neural network optimized by ring topology adaptive differential evolution algorithm[J]. Journal of Dalian Maritime University, 2021 , 47(1) : 101 -110 . DOI: 10.16411/j.cnki.issn1006-7736.2021.01.012
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