|
|
Review and Comparison Between Different Surrogate Models For Analysis of Catalytic Fixed-Bed Reactor
|
|
|
DOR
|
20.1001.2.9919199705.1399.11.1.416.1
|
نویسنده
|
- - ,- - ,- -
|
منبع
|
كنگره مهندسي شيمي - 1399 - دوره : 11 - یازدهمین کنگره بین المللی مهندسی شیمی - کد همایش: 99191-99705
|
|
|
چکیده
|
The need for accurate, fast and low-cost methods to predict characteristics of complex chemical reactions has led to the use of various models in fields of science and engineering# chemical engineering and its subcategories are not excluded from this rule# in chemical engineering, surrogate models are used for various purposes, including modeling, optimization and, etc# latin hypercube is used as a promised sampling method since it has better performance compared to other sampling techniques based on our previous study# in the current study different types of alternative models: linear regression, support vector regression (svr), multi-layer perceptron neural network (mlp), radial neural network are studied and compared based on error rates# results indicated that mlp provides the best ability to predict the steady-state behavior temperature, pressure, mole fraction of components, maximum temperature of a direct dimethyl ether synthesis in the fixed-bed reactor#
|
کلیدواژه
|
Modeling ,Dimethyl-Ether ,Machine Learning ,Surrogate Models
|
آدرس
|
Ferdowsi University Of Mashhad, Iran, Ferdowsi University Of Mashhad, Iran, Research Institute Of Petroleum Industry(Ripi), Iran
|
|
|
|
|
|
|
|
|
|
|
|
|
|
Authors
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|