Using machine learning to predict processes and morphometric features of watershed.

ABSTRACT: The research aims to classify alluvial fans' morphometric properties using the SOM algorithm. It also determines the relationship between morphometric characteristics and erosion rate and lithology using the GMDH algorithm. For this purpose, alluvial fans of 4 watersheds in Iran are extracted semi-automatically using GIS and digital elevation model (DEM) analysis. The relationships between 25 morphometric features of these watersheds, the amount of erosion, and formation material are investigated using the self-organizing map (SOM) method. Principal component analysis (PCA), Greedy, Best first, Genetic search, Random search as feature selection algorithms are used to select the most important parameters affecting erosion and formation material. The group method of data handling (GMDH) algo

SUBMITTER: Mokarram M 

PROVIDER: S-EPMC10212989 | biostudies-literature | 2023 May

REPOSITORIES: biostudies-literature