Ore Grade Estimation in Mining Industry from petro-physical data using neural networks-Reference-Cited by-同舟云学术

Ore Grade Estimation in Mining Industry from petro-physical data using neural networks

Published:2022-12-23 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 4th International Conference on Information Management & Machine Intelligence
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Author:

Nagpal Gaurav¹^ORCID,Ramesh Singh Shrikant²^ORCID,Krishna Jasti Naga Vamsi³^ORCID,Nagpal Ankita⁴^ORCID,Sharma Gunjan Mohan⁵^ORCID

Affiliation:

1. BITS Pilani, India

2. Business Excellence, Hindustan Zinc Limited, India and BITS Pilani, India

3. Department of Core Engineering, BITS Pilani, India

4. Department of Management, BITS Pilani, India

5. Jindal Global University, India

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3590837.3590954

Reference13 articles.

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3. Application of manufacturing management and improvement methodologies in the southern African mining industry

4. Britton , S.G. ( 2016 ). Using lean six sigma techniques to prioritize and define business value for projects at a mature uranium mine and mill . 2016 SME Annual Conference and Expo: The Future for Mining in a Data-Driven World , pp. 188 - 191 Britton, S.G. (2016). Using lean six sigma techniques to prioritize and define business value for projects at a mature uranium mine and mill. 2016 SME Annual Conference and Expo: The Future for Mining in a Data-Driven World, pp. 188-191

5. Dunstan , K. , Lavin , B. , Sanford , R. ( 2006 ). The application of lean manufacturing in a mining environment . Australasian Institute of Mining and Metallurgy Publication Series , pp. 145 - 157 Dunstan, K., Lavin, B., Sanford, R. (2006). The application of lean manufacturing in a mining environment. Australasian Institute of Mining and Metallurgy Publication Series, pp. 145-157