Prediction of Aircraft Cabin Energy Consumption Based on PSO and CRO Algorithms

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 meet the requirements of the rapidity and the accuracy of the aircraft cabin energy consumption prediction for bridge-load air conditioner when an aircraft berthing, a forecasting method based on the combination of neural network, particle swarm and coral reef is proposed. The energy consumption prediction model is established based on wavelet neural network, and the prediction model parameters are optimized using the united algorithm of coral reefs and particle swarm optimization. The united algorithm adopts a double-layer structure: the data of the first layer are grouped and optimized by the particle swarm optimization algorithm for a preliminary optimization, and the first layer optimization results are put into the second layer; the second layer makes use of coral reef algorithm for further optimization, so as to improve the prediction accuracy and solve the problem of slow convergence rate and easy to fall into local extremum. The simulation results show that the proposed united algorithm can effectively improve the prediction speed and accuracy of energy consumption.

Recommended Citation

Wang, Xiuyan; Liu, Yanmin; Zhang, Gewen; Li, Zongshuai; and Lin, Jiaquan (2019) "Prediction of Aircraft Cabin Energy Consumption Based on PSO and CRO Algorithms," Journal of System Simulation: Vol. 30: Iss. 8, Article 31.
DOI: 10.16182/j.issn1004731x.joss.201808031
Available at: https://dc-china-simulation.researchcommons.org/journal/vol30/iss8/31

First Page

3074

DOI Link

https://doi.org/10.16182/j.issn1004731x.joss.201808031

Last Page

3081

CLC

TH137.8

Recommended Citation

Wang Xiuyan, Liu Yanmin, Zhang Gewen, Li Zongshuai, Lin Jiaquan. Prediction of Aircraft Cabin Energy Consumption Based on PSO and CRO Algorithms[J]. Journal of System Simulation, 2018, 30(8): 3074-3081.

DOI

10.16182/j.issn1004731x.joss.201808031