Ataollah Shirzadi

Orcid: 0000-0001-9668-8687

Affiliations:
  • University of Kurdistan, Faculty of Natural Resources, Sanandaj, Iran


According to our database1, Ataollah Shirzadi authored at least 20 papers between 2017 and 2023.

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

Timeline

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Bibliography

2023
Landslide Susceptibility Mapping in a Mountainous Area Using Machine Learning Algorithms.
Remote. Sens., June, 2023

2022
A Robust Deep-Learning Model for Landslide Susceptibility Mapping: A Case Study of Kurdistan Province, Iran.
Sensors, 2022

Swarm intelligence optimization of the group method of data handling using the cuckoo search and whale optimization algorithms to model and predict landslides.
Appl. Soft Comput., 2022

2021
Performance Evaluation of Sentinel-2 and Landsat 8 OLI Data for Land Cover/Use Classification Using a Comparison between Machine Learning Algorithms.
Remote. Sens., 2021

2020
Hybrid Computational Intelligence Methods for Landslide Susceptibility Mapping.
Symmetry, 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

GIS-Based Machine Learning Algorithms for Gully Erosion Susceptibility Mapping in a Semi-Arid Region of Iran.
Remote. Sens., 2020

Daily Water Level Prediction of Zrebar Lake (Iran): A Comparison between M5P, Random Forest, Random Tree and Reduced Error Pruning Trees Algorithms.
ISPRS Int. J. Geo Inf., 2020

Performance Evaluation and Comparison of Bivariate Statistical-Based Artificial Intelligence Algorithms for Spatial Prediction of Landslides.
ISPRS Int. J. Geo Inf., 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

Towards an Ensemble Machine Learning Model of Random Subspace Based Functional Tree Classifier for Snow Avalanche Susceptibility Mapping.
IEEE Access, 2020

2019
A Novel Ensemble Artificial Intelligence Approach for Gully Erosion Mapping in a Semi-Arid Watershed (Iran).
Sensors, 2019

Erratum: Dieu, T.B. et al. A Novel Integrated Approach of Relevance Vector Machine Optimized by Imperialist Competitive Algorithm for Spatial Modeling of Shallow Landslides. <i>Remote Sens.</i> 2018, <i>10</i>, 1538.
Remote. Sens., 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

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

A Novel Integrated Approach of Relevance Vector Machine Optimized by Imperialist Competitive Algorithm for Spatial Modeling of Shallow Landslides.
Remote. Sens., 2018

Landslide Detection and Susceptibility Mapping by AIRSAR Data Using Support Vector Machine and Index of Entropy Models in Cameron Highlands, Malaysia.
Remote. Sens., 2018

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


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