Conjunct applicability of MCDM-based machine learning algorithms in mapping the sediment formation potential

Summary

Abstract This study evaluates the applicability of multicriteria decision-making (MCDM) methods, including SAW, VIKOR, TOPSIS, and Condorcet algorithm based on game theory and machine learning algorithms (MLAs) including K-nearest neighbor, Naïve Bayes, Random Forest (RF), simple linear regression and support vector machine in spatial mapping of sediment formation potential in Talar watershed, Iran. In the first approach, MCDM was used, including SAW, VIKOR, TOPSIS, and Condorcet’s algorithm based on game theory. To this end, a decision matrix for MCDM was first created based on the factors affecting sediment formation potential. In the next step, various MLAs were used to construct a distribution map of sediment formation potential. Finally, a distribution map of sediment formation potent