基于改进协同PSO的神经网络飞机客舱能耗预测

doi:10.16182/j.issn1004731x.joss.201804040

系统仿真学报 ›› 2018, Vol. 30 ›› Issue (4): 1535-1541.doi: 10.16182/j.issn1004731x.joss.201804040

基于改进协同PSO的神经网络飞机客舱能耗预测

王修岩, 刘艳敏, 张革文, 李宗帅, 林家泉

中国民航大学电子信息与自动化学院,天津 300300

收稿日期:2016-05-03 修回日期:2016-07-14 出版日期:2018-04-08 发布日期:2019-01-04
作者简介:王修岩(1965-),男,吉林农安,博士,教授,研究方向为非线性系统建模与控制;刘艳敏(1990-),女,山东临沂,硕士,研究方向为非线性系统建模。
基金资助:
国家自然科学基金(U1433107)

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

Wang Xiuyan, Liu Yanmin, Zhang Gewen, Li Zongshuai, Lin Jiaquan

Civil Aviation University of China, College of Electronic Information and Automation, Tianjin 300300, China

Received:2016-05-03 Revised:2016-07-14 Online:2018-04-08 Published:2019-01-04

摘要/Abstract

摘要： 为了正确评估飞机客舱的能耗需求,针对飞机客舱能耗预测时对精度要求较高的问题,提出了改进微粒群算法优化神经网络参数的能耗预测方法。该方法将协同微粒群优化算法和混沌映射微粒群优化算法相结合,在协同微粒群优化算法的基础之上引入混沌思想。利用混沌优化方法的持续搜索能力克服协同优化算法容易陷入局部极值的问题。神经网络的参数通过改进微粒群算法优化以后,能够加快客舱预测的收敛速度,提高预测精度。通过仿真验证了该预测方法的有效性和可行性。

关键词: 改进协同PSO, 神经网络, 飞机客舱, 能耗预测

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.

Key words: improved cooperative PSO, neural network, aircraft cabin, energy consumption prediction

中图分类号:

TH137.8

王修岩, 刘艳敏, 张革文, 李宗帅, 林家泉. 基于改进协同PSO的神经网络飞机客舱能耗预测[J]. 系统仿真学报, 2018, 30(4): 1535-1541.

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.

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基于改进协同PSO的神经网络飞机客舱能耗预测

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

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