基于多元逐步回归和反向传播方法的粗汽油干点软测量模型  

Soft-sensor model based on multiple stepwise regression method and back propagation method

作　　者：陈云[1] 吕翠英[1] 

机构地区：[1]华南理工大学应用数学系,广东广州510641

出　　处：《计算机与应用化学》2003年第6期845-847,共3页Computers and Applied Chemistry

基　　金：广东省自然科学基金(960265)

摘　　要：建立了粗汽油干点软测量模型。模型分别采用多元逐步回归方法和反向传播方法。结果表明:多元逐步回归方法可筛选自变量,但会将一些重要因素剔除;而神经网络可通过预选输入单元确定网络结构。通过对建立好的模型进行预测,可获得较满意的粗汽油干点值。This paper set up soft-sensor model of crude gasoline endpoint. The model used multiple stepwise regression method and back propagation method independently. The result showed that the multiple stepwise regression method could make a selection from many free variables, but it could get rid of some important factors; and the neural network could decide the structure of network by pre-input units. We got a good estimation of crude gasoline endpoint by the model.

关 键 词：多元逐步回归 反向传播方法 粗汽油干点 软测量 模型 产品质量 

分 类 号：TE626.21[石油与天然气工程—油气加工工程]