Machine Learning Approaches for Forecasting Apple and Rice Yield with Impact of Climate Change under Temperate Conditions

dc.contributor.guide	Nageena Nazir
dc.coverage.spatial
dc.creator.researcher	Ume Kulsum
dc.date.accessioned	2026-01-07T10:11:07Z
dc.date.available	2026-01-07T10:11:07Z
dc.date.awarded	2025
dc.date.completed	2025
dc.date.registered	2021
dc.description.abstract	newline
dc.description.note
dc.format.accompanyingmaterial	DVD
dc.format.dimensions
dc.format.extent
dc.identifier.researcherid
dc.identifier.uri	http://hdl.handle.net/10603/686613
dc.language	English
dc.publisher.institution	Division of Agricultural Statistics
dc.publisher.place	Srinagar
dc.publisher.university	Sher E Kashmir University of Agricultural Science and Technology of Kashmir, Srinagar
dc.relation
dc.rights	university
dc.source.university	University
dc.subject.keyword	Agricultural Sciences
dc.subject.keyword	Agriculture Multidisciplinary
dc.subject.keyword	Life Sciences
dc.title	Machine Learning Approaches for Forecasting Apple and Rice Yield with Impact of Climate Change under Temperate Conditions
dc.title.alternative
dc.type.degree	Ph.D.