Prediction of gross calorific value as a function of proximate parameters for Jharia and Raniganj coal using machine learning based regression methods-Reference-Cited by-同舟云学术

Prediction of gross calorific value as a function of proximate parameters for Jharia and Raniganj coal using machine learning based regression methods

Published:2021-10-26 Issue: Volume: Page:1-14
ISSN:1939-2699
Container-title:International Journal of Coal Preparation and Utilization
language:en
Short-container-title:International Journal of Coal Preparation and Utilization

Author:

Mondal Chinmay¹^ORCID,Pandey Aditya¹^ORCID,Pal Samir Kumar¹,Samanta Biswajit¹,Dutta Dibyendu²

Affiliation:

1. Department of Mining Engineering, Indian Institute of Technology Kharagpur, Kharagpur, India

2. Regional Remote Sensing Centre-East, NRSC (Indian Space Research Organisation), Kolkata, India

Funder

funding

Publisher

Informa UK Limited

Subject

Mechanical Engineering,Energy Engineering and Power Technology,Geotechnical Engineering and Engineering Geology,Fuel Technology,General Chemical Engineering

Link

https://www.tandfonline.com/doi/pdf/10.1080/19392699.2021.1995376

Reference36 articles.

1. Prediction of gross calorific value of coal based on proximate analysis using multiple linear regression and artificial neural networks

2. Linear regression-based correlations for estimation of high heating values of Pakistani lignite coals

3. Proximate analysis based multiple regression models for higher heating value estimation of low rank coals

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