Khabat Khosravi

Orcid: 0000-0001-5773-4003

According to our database1, Khabat Khosravi authored at least 13 papers between 2017 and 2022.

Collaborative distances:
  • Dijkstra number2 of five.
  • Erdős number3 of four.

Timeline

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Bibliography

2022
Stacking ensemble-based hybrid algorithms for discharge computation in sharp-crested labyrinth weirs.
Soft Comput., 2022

Intelligent flow discharge computation in a rectangular channel with free overfall condition.
Neural Comput. Appl., 2022

Evaluation of deep machine learning-based models of soil cumulative infiltration.
Earth Sci. Informatics, 2022

2021
Predicting stable gravel-bed river hydraulic geometry: A test of novel, advanced, hybrid data mining algorithms.
Environ. Model. Softw., 2021

2020
Flood Detection and Susceptibility Mapping Using Sentinel-1 Remote Sensing Data and a Machine Learning Approach: Hybrid Intelligence of Bagging Ensemble Based on K-Nearest Neighbor Classifier.
Remote. Sens., 2020

A novel ensemble learning based on Bayesian Belief Network coupled with an extreme learning machine for flash flood susceptibility mapping.
Eng. Appl. Artif. Intell., 2020

Shear Stress Distribution Prediction in Symmetric Compound Channels Using Data Mining and Machine Learning Models.
CoRR, 2020

2019
Shallow Landslide Prediction Using a Novel Hybrid Functional Machine Learning Algorithm.
Remote. Sens., 2019

Flood Spatial Modeling in Northern Iran Using Remote Sensing and GIS: A Comparison between Evidential Belief Functions and Its Ensemble with a Multivariate Logistic Regression Model.
Remote. Sens., 2019

Meteorological data mining and hybrid data-intelligence models for reference evaporation simulation: A case study in Iraq.
Comput. Electron. Agric., 2019

2018
Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping.
Sensors, 2018

Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms.
Sensors, 2018

2017
A novel hybrid artificial intelligence approach for flood susceptibility assessment.
Environ. Model. Softw., 2017


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