Dataset for: Predictive analysis of gas holdup in bubble column using machine learning methods
Published: 28 April 2022| Version 1 | DOI: 10.17632/s3wjhzzdr3.1
Contributors:
Sumit Hazare,
,
,
,
,
,
Description
Dataset for: Predictive analysis of gas holdup in bubble column using machine learning methods The dataset used for the prediction of gas holdup in bubble column using machine learning methods: Artificial Neural Network, Extra Trees, Random Forest, and Support Vector Regression. Data is extracted from literature with the help of the Engauge Digitizer extraction tool. Data contains gas holdup as the target/dependent variable and 14 independent variables which are used for the prediction of the gas holdup. A detailed description of the methods used with optimized hyperparameters is present in the article submitted to ChERD which is in process.
Files
Institutions
Institute of Chemical Technology
Categories
Chemical Engineering, Machine Learning, Bubble Column