المؤلفون: Kwesi Twum Antwi-Agyakwa, Mawuli Kwaku Afenyo, Donatus Bapentire Angnuureng

المصدر: Water; Volume 15; Issue 3; Pages: 427

مصطلحات موضوعية: flood prediction tools, bibliometric analysis, machine learning, numerical model, probabilistic model, Scopus, GIS, flood hazard, meta-analysis, Biblioshiny

جغرافية الموضوع: agris

وصف الملف: application/pdf

Relation: Hydrology; https://dx.doi.org/10.3390/w15030427

الاتاحة: https://doi.org/10.3390/w15030427

المؤلفون: Kwesi Twum Antwi-Agyakwa, Mawuli Kwaku Afenyo, Donatus Bapentire Angnuureng

المصدر: Water, Vol 15, Iss 3, p 427 (2023)

مصطلحات موضوعية: flood prediction tools, bibliometric analysis, machine learning, numerical model, probabilistic model, Scopus, Hydraulic engineering, TC1-978, Water supply for domestic and industrial purposes, TD201-500

Relation: https://www.mdpi.com/2073-4441/15/3/427; https://doaj.org/toc/2073-4441; https://doaj.org/article/2913eca41b57437f9fd8f2fa21301397

الاتاحة: https://doi.org/10.3390/w15030427
https://doaj.org/article/2913eca41b57437f9fd8f2fa21301397

المؤلفون: Kwesi Twum Antwi-Agyakwa, Mawuli Kwaku Afenyo, Donatus Bapentire Angnuureng

المصدر: Water, Vol 15, Iss 427, p 427 (2023)

مصطلحات موضوعية: flood prediction tools, bibliometric analysis, machine learning, numerical model, probabilistic model, Scopus, Hydraulic engineering, TC1-978, Water supply for domestic and industrial purposes, TD201-500, envir, geo

Relation: https://doi.org/10.3390/w15030427

الاتاحة: https://doi.org/10.3390/w15030427