What is he best known for?
The fields of study he is best known for:
- Statistics
- Erosion
- Machine learning
His main research concerns Topographic Wetness Index, Landslide, Cartography, Receiver operating characteristic and Hydrology.
He interconnects Stream power, Random forest, Flood myth and Bivariate analysis in the investigation of issues within Topographic Wetness Index.
His studies deal with areas such as Artificial neural network, Support vector machine, Statistics, Altitude and Normalized Difference Vegetation Index as well as Landslide.
Hamid Reza Pourghasemi interconnects Watershed, Kernel, Field and Radial basis function in the investigation of issues within Cartography.
His Receiver operating characteristic research includes elements of Elevation and Statistical model.
Hamid Reza Pourghasemi has included themes like Soil texture and Analytic hierarchy process in his Hydrology study.
His most cited work include:
- Application of fuzzy logic and analytical hierarchy process (AHP) to landslide susceptibility mapping at Haraz watershed, Iran (475 citations)
- Landslide susceptibility mapping using certainty factor, index of entropy and logistic regression models in GIS and their comparison at Mugling–Narayanghat road section in Nepal Himalaya (358 citations)
- Landslide susceptibility mapping at Golestan Province, Iran: A comparison between frequency ratio, Dempster-Shafer, and weights-of-evidence models (262 citations)
What are the main themes of his work throughout his whole career to date?
His scientific interests lie mostly in Landslide, Topographic Wetness Index, Hydrology, Receiver operating characteristic and Statistics.
His Landslide research incorporates themes from Cartography, Bivariate analysis, Artificial neural network and Field.
His Topographic Wetness Index research incorporates elements of Stream power, Groundwater, Altitude, Random forest and Normalized Difference Vegetation Index.
His Hydrology research is multidisciplinary, incorporating elements of Soil texture, Land use and Geographic information system.
The various areas that Hamid Reza Pourghasemi examines in his Receiver operating characteristic study include Analytic hierarchy process, Support vector machine and Stage.
His research in Statistics focuses on subjects like Flood myth, which are connected to Flooding.
He most often published in these fields:
- Landslide (29.79%)
- Topographic Wetness Index (28.51%)
- Hydrology (24.26%)
What were the highlights of his more recent work (between 2019-2021)?
- Landslide (29.79%)
- Statistics (20.00%)
- Random forest (18.72%)
In recent papers he was focusing on the following fields of study:
Hamid Reza Pourghasemi mainly investigates Landslide, Statistics, Random forest, Support vector machine and Artificial intelligence.
He has researched Landslide in several fields, including Cartography, Watershed, Flood myth and Normalized Difference Vegetation Index.
He combines subjects such as TOPSIS and Geographic information system with his study of Statistics.
Hamid Reza Pourghasemi frequently studies issues relating to Topographic Wetness Index and Random forest.
His research integrates issues of Principle of maximum entropy, Elastic net regularization, Multivariate statistics, Algorithm and Receiver operating characteristic in his study of Support vector machine.
His Artificial intelligence research includes themes of Machine learning and Groundwater.
Between 2019 and 2021, his most popular works were:
- Assessing and mapping multi-hazard risk susceptibility using a machine learning technique. (37 citations)
- How do machine learning techniques help in increasing accuracy of landslide susceptibility maps (36 citations)
- A machine learning framework for multi-hazards modeling and mapping in a mountainous area. (30 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Machine learning
- Erosion
The scientist’s investigation covers issues in Support vector machine, Landslide, Artificial intelligence, Statistics and Topographic Wetness Index.
His research investigates the connection with Support vector machine and areas like Receiver operating characteristic which intersect with concerns in Mean squared error and Random forest.
The Landslide study combines topics in areas such as Cartography, Watershed and Flood myth.
His Artificial intelligence research focuses on Machine learning and how it relates to Altitude.
His work on Generalized linear model and Principle of maximum entropy as part of his general Statistics study is frequently connected to Adaptive neuro fuzzy inference system, thereby bridging the divide between different branches of science.
He works mostly in the field of Topographic Wetness Index, limiting it down to concerns involving Algorithm and, occasionally, Elastic net regularization and Drainage density.
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