Predictive modeling of biomass gasification with machine learning-based regression methods

Furkan Elmaz; Özgün Yücel; Ali Yener Mutlu

doi:10.1016/j.energy.2019.116541

ScienceGate Book Chapters

JOURNAL ARTICLE

Predictive modeling of biomass gasification with machine learning-based regression methods

Furkan Elmaz Özgün Yücel Ali Yener Mutlu

Year: 2019 Journal: Energy Vol: 191 Pages: 116541-116541 Publisher: Elsevier BV

DOI: 10.1016/j.energy.2019.116541

Get Full-Text PDF Get Analytical Report

Keywords:

Multicollinearity Decision tree Support vector machine Regression Regression analysis Machine learning Multilayer perceptron Computer science Polynomial regression Usability Kriging Cross-validation Data mining Artificial intelligence Statistics Mathematics Artificial neural network

Metrics

254

Cited By

8.41

FWCI (Field Weighted Citation Impact)

Refs

0.98

Citation Normalized Percentile

Is in top 1%

Is in top 10%

Citation History

Topics

Thermochemical Biomass Conversion Processes

Physical Sciences → Engineering → Biomedical Engineering

Iron and Steelmaking Processes

Physical Sciences → Engineering → Mechanical Engineering

Energy and Environment Impacts

Physical Sciences → Environmental Science → Pollution

Predictive modeling of biomass gasification with machine learning-based regression methods

Metrics

Citation History

Topics

Related Documents

Machine learning modeling of supercritical water gasification for predictive hydrogen production from waste biomass

Physics-informed machine learning methods for biomass gasification modeling by considering monotonic relationships

Equilibrium modeling and regression analysis of biomass gasification

Machine Learning for Predictive Modeling of Co-gasification: A Step Toward Industry 4.0 in Biomass Waste Valorization

A machine learning based regression methods to predicting syngas composition for plasma gasification system