摘要
对A380在机坪泊位期间客舱内部环境变化情况进行研究,分析影响A380舱内的热环境的主要因子并建立因子模型,采集A380机舱内的大量温度数据,通过分析建立了机舱内热环境预测模型;并在此模型基础上,采用多聚合过程神经元的BP神经网络,对机舱内热环境算子和历史数据进行非线性聚合、分析和学习,最终实现对机舱内的温度的变化进行准确预测,此模型将为舱内热环境控制算法的研究提供一个良好的平台。
Studied the change of passenger cabin environment during the ramp berth of A380,analyzed the main factors that affect the thermal environment of A380 cabin and built factor model,collected temperature data of A380 cabin,and established the predict models of thermal environment through analyze the data.Based on this model,nonlinear aggregation,analyze,study and predict changes in the cabin the cabin temperature curve on the cabin environment operators and historical data with BP neural network of multi-polymerization process neurons and actually predicted the change trend of temperature of the cabin,this model can provide a good platform for the study of cabin thermal environment control algorithm.
出处
《计算机测量与控制》
北大核心
2014年第12期3891-3893,共3页
Computer Measurement &Control
基金
中央高校基本科研业务费专项资金(ZXH2012G005)
中国民用航空局科技基金项目(MHRD0609)
关键词
A380
热环境
多聚合过程神经元
模型
BP
算子
A380
thermal environment
multi-aggregation process neuron
model
BP
operator
