摘要
合成胶乳是一种非牛顿型流体，其表观粘度与温度、固含量、流动状态等因素有关。目前见诸文献报道的一般为粘度与固含量的单变量关联式［１］。利用数学回归方法和人工神经网络方法对合成胶乳实验数据进行处理，获得了在一定温度下描述某类合成胶乳粘度特性的两变量半经验关联式。
Synthetic latex is a kind of non Newton fluid, and its apparent viscosity is related with the temperature, solid content and flowing state. The common reported data fitting formulas depend on a single variable. Using regression analysis and ANN method, we deal with experiment data of some synthetic latex, and obtain a formula with two variables under certain temperature.
出处
《南京化工大学学报》
1998年第3期60-64,共5页
Journal of Nanjing University of Chemical Technology(Natural Science Edition)
关键词
合成胶乳
半经验模型
回归分析
ANN
粘度
synthetic latex semi empirical model regression analysis artificial neural network
