Khabat Khosravi
Ferdowsi University of Mashhad
82 Papers
32 Citations
Khabat Khosravi is an academic researcher from Ferdowsi University of Mashhad. The author has contributed to research in topics: Computer science & Topographic Wetness Index. The author has an hindex of 30, co-authored 62 publications. Previous affiliations of Khabat Khosravi include Virginia Tech College of Natural Resources and Environment & Florida International University.
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Papers
Shear stress distribution prediction in symmetric compound channels using data mining and machine learning models
Zohreh Sheikh Khozani,Khabat Khosravi,Mohammadamin Torabi,Amir Mosavi,Amir Mosavi,Bahram Rezaei,Timon Rabczuk +6 more
TL;DR: In this paper, a set of data mining and machine learning algorithms including Random Forest (RF), M5P, Random Committee, KStar and additive regression implemented on attained data to predict the shear stress distribution in the compound channel.
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Clear-water scour depth prediction in long channel contractions: Application of new hybrid machine learning algorithms
TL;DR: In this paper, the authors evaluated the predictive power of a range of standalone and hybrid machine learning models, including Isotonic Regression (ISOR), Sequential Minimal Optimization (SMO), Iterative Classifier Optimizer (ICO), Locally Weighted Learning (LWL) and Least Median of Squares Regression(LMS) algorithms.
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Suspended sediment load prediction using hybrid bagging-based heuristic search algorithm
TL;DR: In this article , the boosting of two base models, including a Heuristic Search Algorithm for finding the k shortest paths (K*) and an alternating model tree (AM Tree) through combining bagging (BA), dagging (DA), and random subspace (RS) hybridize models, to predict monthly suspended sediment load (SSL) in subtropical monsoon climatic regions.
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Assessment of Geostatistical Methods for Determining Distribution Patterns of Groundwater Resources in Sari-Neka Coastal Plain, Northern Iran
Khabat Khosravi,Mahmoud Habibnejad Roshan,Atta Safari +2 more
- 01 Jul 2017
TL;DR: In this paper, the authors evaluated the temporal change and accuracy of interpolation techniques used for spatial zonation of two groundwater quantity parameters including water table and depth to water table over 11 years.
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