LLM-driven semantic explanations for soil moisture prediction models

Efficient soil moisture prediction is crucial for sustainable agricultural practices, especially in the face of climate change and increasing water scarcity. However, the adoption of machine learning (ML) models in this context is frequently limited by their lack of interpretability, particularly am...

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Bibliographic Details
Main Authors: Bamory Ahmed Toru Koné, Khouloud Boukadi, Rima Grati, Emna Ben Abdallah, Massimo Mecella
Format: Article
Language:English
Published: Elsevier 2025-12-01
Series:Smart Agricultural Technology
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Online Access:http://www.sciencedirect.com/science/article/pii/S277237552500406X
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