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Cited by 958

The DOI matches its Crossref record; 26 of the 26 references it cites were found in a registry or an index.

Advanced Modelling of Soil Organic Carbon Content in Coal Mining Areas Using Integrated Spectral Analysis: A Dengcao Coal Mine Case Study

Open access
Ammara, Gill, NIE, Xiaojun, -hua LIU, Chang·2024·International Journal of Innovative Science and Research Technology (IJISRT)
DOI 10.38124/ijisrt/ijisrt24may2382
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Abstract

Effective modelling and integrated spectral analysis approaches can advance modelling precision. To develop an integrated spectral forecast modelling of soil organic carbon (SOC), this research investigated a mining coal in Dengcao Coal Mine Area, Zhengzhou. The study utilizes the Lasso and Ranger algorithms were utilized in spectral band analysis. Four primary models employed during this process include Artificial Neural Network (ANN), Support Vector Machine, Random Forest (RF), and Partial Least Squares Regression (PLSR). The ideal model was chosen. The results showed that, in contrast to when band collection was based on Lasso algorithm modelling, model precision was higher when it was based on the Ranger algorithm. ANN model had an ideal goodness acceptance, and the modelling developed by RF showed the steadiest modelling consequences. Based on the results, a distinct method is proposed in this study for band assortment at the earlier stage of integrated spectral modelling of SOC. The Ranger method can be used to check the spectral particles, and RF or ANN can be chosen to develop the prediction modelling based on different statistics sets, which is appropriate to create the prediction modelling of SOC content in Dengcao Coal Mine Area. This research avails a position for the integrated spectral of Analysis for Advanced Modelling of Soil Organic Carbon Content in Coal Sources alongside a theoretical foundation for innovating portable device for the integrated spectral assessment of SOC content in coal mining habitats. This study might be significant for the changing modelling and monitoring of SOC in mining and environmental areas.

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Metadata

Authors
Ammara, G., NIE, X., & -hua LIU, C.
Venue
International Journal of Innovative Science and Research Technology (IJISRT)
Publisher
International Journal of Innovative Science and Research Technology
Published
2024-06-14
Pages
2844-2853
ISSN
2456-2165 (ISSN-L)
DOI
10.38124/ijisrt/ijisrt24may2382
OpenAlex
W4399685394
Cited by
958
References
26
FWCI
112.81
Type
journal article
Language
en
Open access
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CoChat. (2026). Citation check: Advanced Modelling of Soil Organic Carbon Content in Coal Mining Areas Using Integrated Spectral Analysis: A Dengcao Coal Mine Case Study. https://app.cochat.ai/papers/10.38124/ijisrt/ijisrt24may2382
The paper
Ammara, G., NIE, X., & -hua LIU, C. (2024). Advanced Modelling of Soil Organic Carbon Content in Coal Mining Areas Using Integrated Spectral Analysis: A Dengcao Coal Mine Case Study. International Journal of Innovative Science and Research Technology (IJISRT). https://doi.org/10.38124/ijisrt/ijisrt24may2382

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.