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

🤖 Plain-English Summary

Effective modelling and integrated spectral analysis approaches can advance modelling precision. 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.

🔑 Key Findings

• 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).

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