Prediction of HGI of South African coalfields: a comparative application of ANN, SVR and LSTM models-Reference-Cited by-同舟云学术

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Prediction of HGI of South African coalfields: a comparative application of ANN, SVR and LSTM models

Published:2024-04-09 Issue: Volume: Page:1-17
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:

Lawal Abiodun Ismail¹,Bada Samson Oluwaseyi²,Onifade Moshood³

Affiliation:

1. Department of Mining Engineering, Federal University of Technology, Akure, Nigeria

2. School of Chemical and Metallurgy, Faculty of Engineering and the Built Environment, University of the Witwatersrand, Johannesburg, South Africa

3. Institute of Innovation, Science and Sustainability, Federation University Australia, Ballarat, Victoria, Australia

Publisher

Informa UK Limited

Link

https://www.tandfonline.com/doi/pdf/10.1080/19392699.2024.2339319

Reference23 articles.

1. Grindability Studies on Blended Coals of High-Ash Indian Coals with Low-Ash Imported Coals

2. Studies of the relationship between petrography and grindability for Kentucky coals using artificial neural network

3. Prediction of coal grindability based on petrography, proximate and ultimate analysis using multiple regression and artificial neural network models

4. Interrelationships between the Bond Grindability with Physicomechanical and Chemical Properties of Coals

5. A combined experimental and theoretical study on laboratory-scale comminution of coal and biomass blends

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