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Cumulative gangue mixing ratio prediction model for image-based in situ coal/gangue identification

Crossref DOI link: https://doi.org/10.1007/s40571-025-01001-3

Published Print: 2025-08

Update policy: https://doi.org/10.1016/elsevier_cm_policy

Authors

Zhang, Jinwang

Zhao, Jialin

He, Geng

Wan, Xiaohang

Geniş, Melih

Zhang, Haobo

Wei, Weijie

Li, Lianghui

Özarslan, Ahmet

Cheng, Dongliang

Wang, Jingzheng
Funding

Funding for this research was provided by:

Beijing Natural Science Foundation (Grant No. 2232059)

National Natural Science Foundation of China (Grant Nos. 52374148)

National Natural Science Foundation of China (52204163)

National Natural Science Foundation of China (52404159)

National Natural Science Foundation of China (52121003)

Open Fund of Key laboratory of Xinjiang Coal Resources Green Mining, Ministry of Education (Grant No. KLXGY-KB2408)

Fundamental Research Funds for the Central Universities (Grant Nos. 2023JCCXNY04)

Fundamental Research Funds for the Central Universities (2025JCCXNY02)

China Postdoctoral Science Foundation (Grant No. 2024T171006)
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Text and Data Mining valid from 2025-08-01

Text and Data Mining valid from 2025-08-01

Version of Record valid from 2026-01-28
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This article is maintained by: Elsevier

Article Title: Cumulative gangue mixing ratio prediction model for image-based in situ coal/gangue identification

Journal Title: Computational Particle Mechanics

CrossRef DOI link to publisher maintained version: https://doi.org/10.1007/s40571-025-01001-3

Content Type: article

Copyright: Copyright © 2025 The Authors. Published by Elsevier Ltd. Published by Elsevier Ltd