Nonlinear Modeling of Chemical Process using Nonparametric Regressions: Research on Nonparametric Regression Application

Abstract

Multivariate Analysis Modeling like Multiple Regression Analysis has been used for the validation of hypothesis or discovery of new hypothesis. But it is not necessarily a good modeling tool for chemical process because of its strong nonlinearity. Applying Alternate Conditional Expectation to these processes instead of the ordinary least square method sometimes gives informative results to the practitioners. We will discuss two applications : Reactor simulation data to show the nonlinear modeling power of chemical processes and Laboratory data analysis for practical application. This method is a simple extension of ordinary Multiple Regression and practitioners can understand the idea of it. Various applications especially chemical reaction and polymer have been examined.