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Machine Learning-Based Assessment of Watershed Morphometry in Makran

This study proposes an artificial intelligence approach to assess watershed morphometry in the Makran subduction zones of South Iran and Pakistan. The approach integrates machine learning algorithms, including artificial neural networks (ANN), support vector regression (SVR), and multivariate linear...

Ausführliche Beschreibung

Gespeichert in:
Hauptverfasser: Reza Derakhshani, Mojtaba Zaresefat, Vahid Nikpeyman, Amin GhasemiNejad, Shahram Shafieibafti, Ahmad Rashidi, Majid Nemati, Amir Raoof
Format: Artigo
Sprache:Inglês
Veröffentlicht: MDPI AG 2023-03-01
Schriftenreihe:Land
Schlagworte:
watershed morphometry
fuzzy analytic hierarchy process
artificial neural networks
support vector regression
multivariate linear regression
tectonics
Online-Zugang:https://www.mdpi.com/2073-445X/12/4/776
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