摘要
高水分农产品物料的比热是农产品加工工程研究和农产品加工设备设计中的重要热特性参数之一．预测精度关系到所设计加工设备的质量、性能的优劣．本文建立了高水分农产品物料比热的ＢＰ神经网络模型，比较了二元回归模型和ＢＰ神经网络模型对高水分农产品物料比热的预测效果，得到ＢＰ神经网络模型的预测精度高于二元回归模型．
The specific heat of high moisture content farm products is one of the important parameters of thermophysical properties in designing farm products processing equipment. The BP neural network(BPNN) model of the specific heat of farm products with a high moisture content is established, and the calculated precisions between dual regression model and BPNN model are compared. The result shows that the calculated precision is higher for BPNN model than that for dual regression model.
出处
《江苏理工大学学报（自然科学版）》
1999年第1期16-19,共4页
Journal of Jiangsu University of Science and Technology(Natural Science)
关键词
神经网络
农产品
预测
水分
比热
BP神经网络
neural networks
agricultural products
predications/high water content
