Daily soil temperature prediction using hybrid deep learning and SHAP for sustainable soil management
The thermal conditions within soil layers represent essential information across diverse fields including sustainable agriculture, power generation, biological research, ecological studies, forest management, and thermal energy systems. Therefore, this study assessed prediction capabilities for subt...
Saved in:
| Main Authors: | Meysam Alizamir, Kaywan Othman Ahmed, Salim Heddam, Sungwon Kim, Jeong Eun Lee |
|---|---|
| Format: | Article |
| Language: | English |
| Published: |
Taylor & Francis Group
2025-12-01
|
| Series: | Engineering Applications of Computational Fluid Mechanics |
| Subjects: | |
| Online Access: | https://www.tandfonline.com/doi/10.1080/19942060.2025.2541686 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
A Hybrid Wavelet-Based Deep Learning Model for Accurate Prediction of Daily Surface PM<sub>2.5</sub> Concentrations in Guangzhou City
by: Zhenfang He, et al.
Published: (2025-03-01) -
Predicting depression risk in middle-aged and elderly adults in China using CNN-BiLSTM-Attention mechanism and LSTM+SHAP framework
by: Shengxian Bi, et al.
Published: (2025-08-01) -
Developing an efficient explainable artificial intelligence approach for accurate reverse osmosis desalination plant performance prediction: application of SHAP analysis
by: Meysam Alizamir, et al.
Published: (2024-12-01) -
Improving the explainability of CNN-LSTM-based flood prediction with integrating SHAP technique
by: Hao Huang, et al.
Published: (2024-12-01) -
Deep Learning in Finance: A Survey of Applications and Techniques
by: Ebikella Mienye, et al.
Published: (2024-10-01)