Identifying social vulnerability profiles for coastal flood using supervised and unsupervised machine learning: A case study of Lekki Peninsula, Lagos, Nigeria

Coastal flooding disproportionately impacts households based on pre-existing vulnerability characteristics. Identifying these vulnerabilities is critical for effective flood risk reduction. Despite its significance, there is a paucity of techniques for identifying suitable Social Vulnerability Indic...

Celý popis

Podrobná bibliografie

Vydáno v:	International journal of disaster risk reduction Ročník 127; s. 105693
Hlavní autoři:	Akindejoye, Adesola, Viavattene, Christophe, Priest, Sally, Windridge, David
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Elsevier Ltd 01.09.2025
Témata:	Expectation maximization algorithm Permutation feature importance Support vector regression Vulnerability indicators Permutation feature importance Support vector regression Expectation maximization algorithm Vulnerability indicators
ISSN:	2212-4209, 2212-4209
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!