Prediction of coke AMS through data mining: a practical approach-Reference-Cited by-同舟云学术

Prediction of coke AMS through data mining: a practical approach

Published:2020-11-19 Issue: Volume: Page:1-18
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:

Kumar Deepak¹,Saxena V. K.²,Tiwari H. P.³,Aleti B. T.¹,Tiwary V. K.¹

Affiliation:

1. CRMT Lab, R&D and SS, Tata Steel Limited, Jamshedpur, India

2. Department of Fuel, Minerals and Metallurgical Engineering, IIT (ISM), Dhanbad, India

3. Coal and Coke Making Research, R&D, Tata Steel Limited, Jamshedpur, India

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/10.1080/19392699.2020.1845662

Reference14 articles.

1. Coal and Coke for Blast Furnaces.

2. Coal for metallurgical coke production: predictions of coke quality and future requirements for cokemaking

3. Some aspects of deterioration of coke in blast furnace.

4. Programmed heating of coke ovens for increased coke size

5. The evolution of structural order, microstructure and mineral matter of metallurgical coke in a blast furnace: A review

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1. Optimization of Blast Furnace Ironmaking Using Machine Learning and Genetic Algorithms;steel research international;2024-08-22

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