基于模糊径向基函数神经网络的航空煤油干点估计  

Jet Fuel Endpoint Estimation Based on a Fuzzy Radial Basis Function Neural Network

作　　者：刘士荣[1] 郑瑜[1] 骆昕 葛映辉 

机构地区：[1]宁波大学自动化与计算机技术系,浙江宁波315211

出　　处：《机电工程》2000年第3期73-76,共4页Journal of Mechanical & Electrical Engineering

摘　　要：研究以模糊聚类和径向基函数网络结合的模糊径向基函数网络ＦＲＢＦＮ，并用主元分析对高维输入变量进 行预处理，降低了模型的输入变量维数，进而构造基于ＰＣＡ－ＦＲＢＦＮ的估计模型。这一方法通过对加氢裂化装置分 馏塔航空煤油干点估计得到验证。In this paper, a fuzzy radial basis function neural network (FRBFN) is presented, which combining bob fuzzy clustering technique and radial basis function neural network. The principle component analysis (PCA) technique is applied to preprocessing high dimensional input variable so that the dimension of input variable is decreased, and an estimator model based on PCAFRBFN is constructed. This approach has been shown by the example of jet fuel endpoint estimation for a fractionator of the hydrocracking unit in the oil refining industry.

关 键 词：航空煤油 干点估计 径向基函数 神经网络 

分 类 号：TE626.34[石油与天然气工程—油气加工工程]