粮油食品科技2015，Vol.23Issue(1)：94-97,4.
基于 BP神经网络方法的高大平房仓温度场预测研究
Prediction of the temperature field of high & large warehouse based on BP neural network
高松 1宋辉2
作者信息
- 1. 中国建筑科学研究院建筑环境与节能研究院，北京 100013
- 2. 北京工业大学，北京 100124
- 折叠
摘要
Abstract
Large warehouse is the main type of grain granary for state grain depot. In the summer,due to the continuous heat outside,grain pile will reach a higher temperature,moreover,the growth of microor-ganisms will lead to further internal heat for grain heap,which would harm the security of stored grain. In order to safeguard the quality of the stored grain and control the temperature,it is important to research and apply granary temperature field prediction system. BP neural network forecasting model was studied based on neural network model. The actual monitoring data of grain in warehouse were selected to emu-late on MATLAB platform,and construct models. The factors which affected the grain temperature field were analyzed,and the weights of the factors were determined by SPSS statistical software,the results of the principal component analysis were verified by neural network method.关键词
粮食储藏/神经网络/温度场预测Key words
grain storage/neural network/temperature field prediction分类
农业科技引用本文复制引用
高松,宋辉..基于 BP神经网络方法的高大平房仓温度场预测研究[J].粮油食品科技,2015,23(1):94-97,4.
