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SCIESCOPUS
Enhancing spatial prediction of groundwater-prone areas through optimization of a boosting algorithm with bio-inspired metaheuristic algorithmsopen access

Razavi-Termeh, Seyed Vahid; Sadeghi-Niaraki, Abolghasem; Abba, Sani I.; Ali, Farman; Choi, Soo-Mi

ArticleIssue Date2024CitationAPPLIED WATER SCIENCE, v.14, no.11PublisherSPRINGER HEIDELBERG
SCIESCOPUS
Spatio-temporal modeling of asthma-prone areas: Exploring the influence of urban climate factors with explainable artificial intelligence (XAI)

Razavi-Termeh, Seyed Vahid; Sadeghi-Niaraki, Abolghasem; Ali, Farman; Naqvi, Rizwan Ali; Choi, Soo-Mi

ArticleIssue Date2024CitationSustainable Cities and Society, v.116PublisherElsevier Ltd
SCOPUS
Cutting-Edge strategies for absence data identification in natural hazards: Leveraging Voronoi-Entropy in flood susceptibility mapping with advanced AI techniques

Vahid Razavi-Termeh, Seyed; Sadeghi-Niaraki, Abolghasem; Ali, Farman; Ali Naqvi, Rizwan; Choi, Soo-Mi

ArticleIssue Date2025CitationJournal of Hydrology, v.648PublisherElsevier B.V.
SCIESCOPUS
Improving flood-prone areas mapping using geospatial artificial intelligence (GeoAI): A non-parametric algorithm enhanced by math-based metaheuristic algorithms

Razavi-Termeh, Seyed Vahid; Sadeghi-Niaraki, Abolghasem; Ali, Farman; Choi, Soo-Mi

ArticleIssue Date2025CitationJournal of Environmental Management, v.375PublisherAcademic Press
SCIE
Leveraging deep learning for plant disease and pest detection: a comprehensive review and future directionsopen access

Shoaib, Muhammad; Sadeghi-Niaraki, Abolghasem; Ali, Farman; Hussain, Irfan; Khalid, Shah

ArticleIssue Date2025CitationFRONTIERS IN PLANT SCIENCE, v.16PublisherFRONTIERS MEDIA SA
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