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

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.

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• 1 To develop an integrated spectral forecast modelling of soil organic carbon (SOC), this research investigated a mining coal in Dengcao Coal Mine Area, Zhengzhou.
• 2 The study utilizes the Lasso and Ranger algorithms were utilized in spectral band analysis.
• 3 Four primary models employed during this process include Artificial Neural Network (ANN), Support Vector Machine, Random Forest (RF), and Partial Least Squares Regression (PLSR).

This research advances how AI systems learn, reason, and solve problems — with direct implications for automation and scientific discovery.

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