An explainable and auditable IoT–AI engineering framework for soil–environment regime discovery in arid agriculture

Sustainable crop planning in arid and semi-arid regions is constrained by soil degradation, water scarcity, and high environmental variability, while the adoption of data-driven decision methods remains limited by poor transparency and trust. This study investigates whether unsupervised soil–environ...

Бүрэн тодорхойлолт

Номзүйн дэлгэрэнгүй

Үндсэн зохиолчид:	May Alashwal, Huma Jamshed, Mohammed Algarni, Urooj Waheed, Mohammed Zwawi, Ahmad Hussain
Формат:	Artigo
Хэл сонгох:	Inglês
Хэвлэсэн:	Elsevier 2026-12-01
Цуврал:	Results in Engineering
Нөхцлүүд:	Explainable artificial intelligence (XAI) Unsupervised learning Soil–environment zoning Soil–environment regime discovery Arid Semi-arid agriculture
Онлайн хандалт:	http://www.sciencedirect.com/science/article/pii/S2590123026027301
Шошгууд:	Шошго нэмэх Шошго байхгүй, Энэхүү баримтыг шошголох эхний хүн болох!