Study on Catalyst Combination for Ethanol Coupling to C4 Olefins Based on Multivariate Ridge Regression Model Fused With Radial Basis Function
Abstract
The effects of different catalyst combinations and temperatures on ethanol conversion and C4 olefin selectivity were
discussed.Firstly,the multivariate ridge regression model based on L2 penalty term is introduced,and the best estimation of ridge
regression is obtained by using the least square method.However,ridge regression always regards this problem as a linear problem.
In order to solve this problem,the radial basis function based on Gaussian kernel is introduced as the basic variable for model
optimization.Finally,the model is solved and the results are obtained.
discussed.Firstly,the multivariate ridge regression model based on L2 penalty term is introduced,and the best estimation of ridge
regression is obtained by using the least square method.However,ridge regression always regards this problem as a linear problem.
In order to solve this problem,the radial basis function based on Gaussian kernel is introduced as the basic variable for model
optimization.Finally,the model is solved and the results are obtained.
Keywords
Ethanol;C4 olefin;Catalyst Combination;Multiple Regression Analysis
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PDFReferences
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DOI: https://doi.org/10.18282/l-e.v10i4.2514
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