Optimization Model Research Based on Partial Least Squares Method

DOI

10.2991/ahis.k.220601.028How to use a DOI?

Keywords

Unary polynomial regression models; Partial least squares; Optimization model; Cross-validity testing

Abstract

In this paper, taking the preparation of C4 olefins by ethanol coupling as an example, we discuss an optimization model based on partial least squares method. First of all, build a univariate polynomial regression model, and analyse the effect of temperature on the selectivity of ethanol conversion and C4 olefins. Secondly, calculate regression equations using partial least squares, and conduct a cross-validity test. The fitting effect is satisfactory; at last, An optimization model is established according to the correlation between the variables, and the catalyst combination and temperature are calculated when the C4 olefin yield is as high as possible. This model is great significant for studying the interdependencies and maximality problems between multiple correlation variables.

Copyright

© 2022 The Authors. Published by Atlantis Press International B.V.

Open Access

This is an open access article distributed under the CC BY-NC 4.0 license.

Download article (PDF)

TY  - CONF
AU  - Huilan Jin
AU  - Zhenrong Zhang
AU  - Liyan Xu
AU  - Hong Fang
PY  - 2022
DA  - 2022/06/02
TI  - Optimization Model Research Based on Partial Least Squares Method
BT  - Proceedings of the 2021 International conference on Smart Technologies and Systems for Internet of Things (STS-IOT 2021)
PB  - Atlantis Press
SP  - 141
EP  - 147
SN  - 2589-4919
UR  - https://doi.org/10.2991/ahis.k.220601.028
DO  - 10.2991/ahis.k.220601.028
ID  - Jin2022
ER  -