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September 23, 2025VIETNAM JOURNAL OF EARTH SCIENCESOpen Access

Prediction of Optimum Water Content of soil using advanced machine learning methods: A comparative study of RF, SVM, and ANN models

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Authors

BPBinh Thai PhamHiroshima UniversityTHTrang Le HuyenVietnam National University, HanoiIPIndra PrakashGeological Survey of India

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Implication

This analysis evaluates Random Forest, SVM, and ANN models for predicting optimum water content in soil samples, indicating RF's superior performance.

Key Points

  • The Random Forest model achieved the highest performance with R2 = 0.84 and RMSE = 1.07%, surpassing other models.
  • Key influencing factors for predicting optimum water content included fines content, plasticity indices, and organic matter.
  • A dataset of over 214 soil samples from Vietnam was used to develop the machine learning models for comparison.
  • Findings suggest that advanced machine learning can simplify the determination of optimum water content in soil.

Cite This Study

Pham et al. (2025) studied this question.

synapsesocial.com/papers/68d4757f31b076d99fa6cd0fhttps://doi.org/10.15625/2615-9783/23484
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