Application of Gauss Process Regression Modeling Based on NN-MIV for Marine Enzyme Fermentation Process
作者单位：School of Electrical and Information Engineering Jiangsu University
会议名称：《第30届中国控制与决策会议》
会议日期：2018年
学科分类：081703[工学-生物化工] 08[工学] 0817[工学-化学工程与技术] 0836[工学-生物工程] 082203[工学-发酵工程] 0822[工学-轻工技术与工程]
基 金：supported by the Priority Academic Program Development of Jiangsu Higher Education Institutions(PAPD 6) Natural Science Foundation of Jiangsu Province of China(BK20130531,BK20151345) Natural Science Research Foundation of Higher Education of Jiangsu Province(17KJB510008) the Initial Research Fund of Highly Specialized Personnel from Jiangsu University(10JDG113)
关 键 词：NN-MIV Gauss Process Regression Marine Enzyme Soft Sensing
摘 要：To overcome the problems of variable redundancy, long training time and low prediction accuracy in the soft sensing model for marine enzyme fermentation, a Gauss process regression（GPR） model based on NN-MIV is presented, which is named as GPR-NNMIV soft sensing model. Firstly, the NN-MIV variable selection method, combining neural network（NN） and mean impact value（MIV）, takes into account both the internal contribution rate and the external contribution rate to get the most suitable input variables with the highest contribution rate, and reduces the number of variables and simplifies soft sensing model. Secondly, based on the NN-MIV method, a new Gauss process regression model is proposed, which does not only give out the soft sensing results but also gives the corresponding uncertainty simultaneously. Results show that the proposed GPR-NNMIV soft sensing model has higher accuracy of results and small confidence intervals compared with single Gauss process model.