Estimation of soil erodibility in Peninsular Malaysia: A case study using multiple linear regression and artificial neural networks

Estimation of soil erodibility in Peninsular Malaysia: A case study using multiple linear regression and artificial neural networks

Soil erodibility (K) is an essential component in estimating soil loss indicating the soil's susceptibility to detach and transport. Data Computing and processing methods, such as artificial neural networks (ANNs) and multiple linear regression (MLR), have proven to be helpful in the developmen...

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Bibliographic Details
Main Authors: Muhammad Ali Rehman, Norinah Abd Rahman, Ahmad Nazrul Hakimi Ibrahim, Norashikin Ahmad Kamal, Asmadi Ahmad
Format: Article
Language:English
Published: Elsevier 2024-04-01
Series:Heliyon
Subjects:
Erodibility
Computational methods
Predictive models
Artificial Neural Network (ANN)
Multiple linear regression (MLR)
Principal Component Analysis (PCA)
Online Access:http://www.sciencedirect.com/science/article/pii/S2405844024048850

Internet

http://www.sciencedirect.com/science/article/pii/S2405844024048850

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