Himan Shahabi

Management, Monitoring, Policy and Law · 2015–2020

A researcher in the Science corpus: 19 papers; trusts 25 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

• Management, Monitoring, Policy and Law — 151 citations into it; #845 of 2,821 by trust here, #198 by citations
• Global and Planetary Change — 141 citations into it; #2,123 of 10,225 by trust here, #745 by citations
• Mechanical Engineering — 68 citations into it
• Artificial Intelligence — 66 citations into it
• Safety, Risk, Reliability and Quality — 58 citations into it
• Environmental Engineering — 35 citations into it
• Water Science and Technology — 29 citations into it
• Atmospheric Science — 26 citations into it

Whom Himan Shahabi trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Biswajeet Pradhan
2. D. Tien Bui
3. Saro Lee
4. Isik Yilmaz
5. Alexander Brenning
6. Wei Chen
7. Binh Thai Pham
8. Khabat Khosravi
9. Haoyuan Hong
10. Leo Breiman

Who trusts Himan Shahabi overall

1. Wei Chen
2. Ataollah Shirzadi
3. D. Tien Bui
4. Khabat Khosravi
5. Qiqing Wang
6. Yongquan Yang
7. Haoyuan Hong
8. Kamran Chapi
9. Binh Thai Pham

Papers from Himan Shahabi's perspective

Ordered by how strongly the researchers Himan Shahabi trusts endorse each paper. Same corpus, a different order for every researcher.

1. Landslide susceptibility mapping using support vector machine and GIS at the Golestan Province, Iran (Proceedings of the Indian Academy of Sciences, Earth and Planetary Sciences)
2. Landslide susceptibility mapping using GIS-based multi-criteria decision analysis, support vector machines, and logistic regression (Landslides)
3. Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China. (Science of the Total Environment)
4. Digital terrain modelling: A review of hydrological, geomorphological, and biological applications
5. Landslide susceptibility mapping : A comparison of logistic regression and neural networks methods in a medium scale study, Hendek Region (Turkey)
6. Assessment of shallow landslide susceptibility using artificial neural networks in Jabonosa River Basin, Venezuela
7. Landslide hazard evaluation: a review of current techniques and their application in a multi-scale study, Central Italy
8. Assessment of landslide susceptibility for a landslide-prone area (north of Yenice, NW Turkey) by fuzzy approach
9. The WEKA data mining software: an update
10. Spatial prediction models for landslide hazards: review, comparison and evaluation

Their papers

• Comparison of Support Vector Machine, Bayesian Logistic Regression, and Alternating Decision Tree Algorithms for Shallow Landslide Susceptibility Mapping along a Mountainous Road in the West of Iran (2020) — 84 citations
• A Hybrid Intelligence Approach to Enhance the Prediction Accuracy of Local Scour Depth at Complex Bridge Piers (2020) — 84 citations
• Shallow Landslide Susceptibility Mapping by Random Forest Base Classifier and Its Ensembles in a Semi-Arid Region of Iran (2020) — 108 citations
• 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 (2020) — 334 citations
• A comparative assessment of flood susceptibility modeling using Multi-Criteria Decision-Making Analysis and Machine Learning Methods (2019) — 629 citations
• New Ensemble Models for Shallow Landslide Susceptibility Modeling in a Semi-Arid Watershed (2019) — 114 citations
• Novel Hybrid Integration Approach of Bagging-Based Fisher’s Linear Discriminant Function for Groundwater Potential Analysis (2019) — 130 citations
• Flood susceptibility mapping at Ningdu catchment, China using bivariate and data mining techniques (2019) — 48 citations
• Spatial prediction of landslide susceptibility by combining evidential belief function, logistic regression and logistic model tree (2019) — 121 citations
• Novel forecasting approaches using combination of machine learning and statistical models for flood susceptibility mapping. (2018) — 336 citations
• GIS-based landslide susceptibility evaluation using a novel hybrid integration approach of bivariate statistical based random forest method (2018) — 257 citations
• A comparative assessment of decision trees algorithms for flash flood susceptibility modeling at Haraz watershed, northern Iran. (2018) — 676 citations
• Mapping Groundwater Potential Using a Novel Hybrid Intelligence Approach (2018) — 184 citations
• Landslide susceptibility modelling using GIS-based machine learning techniques for Chongren County, Jiangxi Province, China. (2018) — 426 citations
• A novel ensemble approach of bivariate statistical-based logistic model tree classifier for landslide susceptibility assessment (2018) — 115 citations
• Landslide susceptibility assessment at the Wuning area, China: a comparison between multi-criteria decision making, bivariate statistical and machine learning methods (2018) — 121 citations
• A novel hybrid artificial intelligence approach for flood susceptibility assessment (2017) — 561 citations
• Remote sensing and GIS-based landslide susceptibility mapping using frequency ratio, logistic regression, and fuzzy logic methods at the central Zab basin, Iran (2015) — 159 citations
• Landslide susceptibility mapping using GIS-based statistical models and Remote sensing data in tropical environment (2015) — 423 citations