Prediction of Aircraft Cabin Energy Consumption Based on Improved Cooperative PSO Neural Network

Authors

Xiuyan Wang, Civil Aviation University of China, College of Electronic Information and Automation, Tianjin 300300, China;
Yanmin Liu, Civil Aviation University of China, College of Electronic Information and Automation, Tianjin 300300, China;
Gewen Zhang, Civil Aviation University of China, College of Electronic Information and Automation, Tianjin 300300, China;
Zongshuai Li, Civil Aviation University of China, College of Electronic Information and Automation, Tianjin 300300, China;
Jiaquan Lin, Civil Aviation University of China, College of Electronic Information and Automation, Tianjin 300300, China;

Abstract

Abstract: To correctly evaluate the energy needs of the aircraft cabin and to predict the energy consumption of the aircraft cabin with higher accuracy, an energy consumption prediction method based on improved particle swarm optimization (PSO) neural network algorithm parameters is proposed. The method combines the cooperative particle swarm optimization algorithm with chaotic particle swarm optimization algorithm. On the basis of cooperative particle swarm optimization algorithm chaos theory is introduced. Continuous search ability by using chaos optimization method to overcome the collaborative optimization algorithm is easy to fall into the local extremum problem. The parameters of the neural network can accelerate the convergence rate of the cabin, and also can improve the accuracy of prediction by improving the particle swarm optimization algorithm. Simulation results verify the validity and feasibility of the proposed method.

Recommended Citation

Wang, Xiuyan; Liu, Yanmin; Zhang, Gewen; Li, Zongshuai; and Lin, Jiaquan (2019) "Prediction of Aircraft Cabin Energy Consumption Based on Improved Cooperative PSO Neural Network," Journal of System Simulation: Vol. 30: Iss. 4, Article 40.
DOI: 10.16182/j.issn1004731x.joss.201804040
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss4/40

First Page

1535

Revised Date

2016-07-14

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201804040

Last Page

1541

CLC

TH137.8

Recommended Citation

Wang Xiuyan, Liu Yanmin, Zhang Gewen, Li Zongshuai, Lin Jiaquan. Prediction of Aircraft Cabin Energy Consumption Based on Improved Cooperative PSO Neural Network[J]. Journal of System Simulation, 2018, 30(4): 1535-1541.

DOI

10.16182/j.issn1004731x.joss.201804040