Product quality prediction in dense medium coal preparation process based on recurrent neural network-Reference-Cited by-同舟云学术

Product quality prediction in dense medium coal preparation process based on recurrent neural network

Published:2023-03-14 Issue:3 Volume:44 Page:291-308
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:

Zhou Chunxia¹²^ORCID,Sun Xiaolu²^ORCID,Shen Yingsong³,Yue Yuanhe⁴,Jing Muyang²,Liang Weinong²,Zhang Haijun¹

Affiliation:

1. School of Chemical Engineering and Technology, China University of Mining and Technology, Xuzhou, China

2. School of Mining and Technology, Inner Mongolia University of Technology, Hohhot, China

3. Department of Coal Beneficiation, Shanxi Tiandi Wangpo Mining Industry Co. Ltd, Zezhou, China

4. School of Energy and Environmental Engineering, Hebei University of Technology, Tianjin, China

Funder

Science and Technology Planning Project of Inner Mongolia Autonomous Region

Basic Scientific Research Expenses Program of Universities Directly under Inner Mongolia Autonomous Region

Natural Science Foundation of Inner Mongolia Autonomous Region

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/10.1080/19392699.2023.2190098

Reference32 articles.

1. Upgrading low-rank coals (Çan, Çanakkale/Turkey) by float-sink separation in dense media

2. Application of artificial neural network to study the performance of multi-gravity separator (MGS) treating iron ore fines

3. Cleaning of Coal by Multi Gravity Separator

4. Prediction of ash content and yield percent of clean coal in multi gravity separator using artificial neural networks

5. Time series prediction method of ash content of dense medium separated clean coal based on EMD-LSTM;Cheng K.;Coal Engineering,2022

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