Kamran Chapi (0000-0002-9466-665X)

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Biography

Dr. Kamran Chapi was born in 1971 in Mahabad, a Kurdish city at west Azarbaijan province, Iran. He received his B.Sc. degree in Rangeland and Watershed Management from Tehran University, Iran in 1995, his M.Sc. in Watershed Engineering from Tarbiat Modarres University, Iran in 1998, and his Ph.D in Water Resources Engineering (Hydrological Modeling) from the University of Guelph, Canada in 2009. He is an associate professor at the Faculty of Natural Resources, University of Kurdistan, Sanandaj, Iran now, teaching hydrology and hydraulic courses in bachelor and master programs. His research interests include hydrological modeling, spatial prediction models for environmental disasters such as floods, landslides and droughts, river engineering, and integrated watershed management.

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University of Kurdistan: Sanandaj, Kurdistan Province, IR

1999-08-25 to present | Associate Professor (Department of Rangeland and Watershed Management)

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Kamran Chapi

https://orcid.org/0000-0002-9466-665X

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Employment (1)

University of Kurdistan: Sanandaj, Kurdistan Province, IR

Education and qualifications (1)

University of Kurdistan: Sanandaj, Kurdistan Province, IR

Works (26)

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

Effects of Inter-Basin Water Transfer on Water Flow Condition of Destination Basin

A Hybrid Computational Intelligence Approach to Groundwater Spring Potential Mapping

Uncertainties of prediction accuracy in shallow landslide modeling: Sample size and raster resolution

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

Shallow Landslide Prediction Using a Novel Hybrid Functional Machine Learning Algorithm

Sinkhole susceptibility mapping: A comparison between Bayes‐based machine learning algorithms

Mapping Groundwater Potential Using a Novel Hybrid Intelligence Approach

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

Landslide Susceptibility Modeling Based on GIS and Novel Bagging-Based Kernel Logistic Regression

Novel GIS Based Machine Learning Algorithms for Shallow Landslide Susceptibility Mapping

A Novel Integrated Approach of Relevance Vector Machine Optimized by Imperialist Competitive Algorithm for Spatial Modeling of Shallow Landslides

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

New Hybrids of ANFIS with Several Optimization Algorithms for Flood Susceptibility Modeling

Land Subsidence Susceptibility Mapping in South Korea Using Machine Learning Algorithms

Quantification of Land use/Land cover change in Qorveh-Dehgolan Basin, Kurdistan Province, Iran Using Remote Sensing and GIS

A comparative study between popular statistical and machine learning methods for simulating volume of landslides

A novel hybrid artificial intelligence approach for flood susceptibility assessment

Non-point source contribution and dynamics of soluble and particulate phosphorus from main tributaries of the Zarivar Lake watershed, Iran

Rock fall susceptibility assessment along a mountainous road: an evaluation of bivariate statistic, analytical hierarchy process and frequency ratio

Shallow landslide susceptibility assessment using a novel hybrid intelligence approach

Flash flood susceptibility analysis and its mapping using different bivariate models in Iran: a comparison between Shannon<sup>’</sup>s entropy, statistical index, and weighting factor models

Excellent approach to modeling urban expansion by Fuzzy Cellular Automata - Agent Base Model

Simulating urban expansion through Cellular Automata model on different neighborhood size

Spatiotemporal patterns of stable isotopes and hydrochemistry in springs and river flow of the upper Karkheh River Basin, Iran

A GIS-based logistic regression model in rock-fall susceptibility mapping along a mountainous road: Salavat Abad case study, Kurdistan, Iran

Peer review (3 reviews for 3 publications/grants)