基于人工神经网络模型的木材干燥应变模拟预测
付宗营,蔡英春,高鑫,周凡,江京辉,周永东

Simulation of Drying Strain Based on Artificial Neural Network Model
Zongying Fu,Yingchun Cai,Xin Gao,Fan Zhou,Jinghui Jiang,Yongdong Zhou
图2 2种干燥基准(S)下干球温度(T)、含水率(MC)和相对湿度(RH)随时间变化曲线
Fig.2 Plots of dry bulb temperature (T), moisture content (MC) and relative humidity (RH)with drying time under two drying schedules (S)