What is he best known for?
The fields of study he is best known for:
- Artificial intelligence
- Statistics
- Machine learning
Biswajeet Pradhan mostly deals with Landslide, Cartography, Geographic information system, Topographic Wetness Index and Hydrology.
The concepts of his Landslide study are interwoven with issues in Logistic regression, Spatial database, Field, Normalized Difference Vegetation Index and Receiver operating characteristic.
His studies in Cartography integrate themes in fields like Landslide susceptibility, Adaptive neuro fuzzy inference system and Natural hazard.
His Geographic information system study incorporates themes from Land cover, Aerial photography, Probabilistic logic and Fuzzy logic.
Biswajeet Pradhan combines subjects such as Data mining, Stream power, Bivariate analysis, Statistics and AdaBoost with his study of Topographic Wetness Index.
His Hydrology study integrates concerns from other disciplines, such as Elevation, Soil map and Land use.
His most cited work include:
- A comparative study on the predictive ability of the decision tree, support vector machine and neuro-fuzzy models in landslide susceptibility mapping using GIS (628 citations)
- Landslide hazard mapping at Selangor, Malaysia using frequency ratio and logistic regression models (557 citations)
- Landslide susceptibility assessment and factor effect analysis: backpropagation artificial neural networks and their comparison with frequency ratio and bivariate logistic regression modelling (540 citations)
What are the main themes of his work throughout his whole career to date?
His primary areas of study are Landslide, Remote sensing, Artificial intelligence, Geographic information system and Hydrology.
Spatial database is closely connected to Cartography in his research, which is encompassed under the umbrella topic of Landslide.
His Remote sensing research is multidisciplinary, incorporating perspectives in Land cover and Terrain.
His work deals with themes such as Machine learning and Pattern recognition, which intersect with Artificial intelligence.
His Topographic Wetness Index research includes themes of Stream power and Normalized Difference Vegetation Index.
His Support vector machine study combines topics in areas such as Decision tree and Artificial neural network.
He most often published in these fields:
- Landslide (35.42%)
- Remote sensing (19.36%)
- Artificial intelligence (21.49%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (21.49%)
- Landslide (35.42%)
- Statistics (19.72%)
In recent papers he was focusing on the following fields of study:
His primary scientific interests are in Artificial intelligence, Landslide, Statistics, Random forest and Deep learning.
Biswajeet Pradhan has researched Artificial intelligence in several fields, including Machine learning and Pattern recognition.
His biological study spans a wide range of topics, including Natural hazard and Topographic Wetness Index.
Biswajeet Pradhan interconnects Meteorology, Physical geography and Land use in the investigation of issues within Landslide.
His Statistics research incorporates elements of Elevation and Lead time.
His Support vector machine research incorporates themes from Decision tree, Data mining and Group method of data handling.
Between 2019 and 2021, his most popular works were:
- Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods. (83 citations)
- Modeling flood susceptibility using data-driven approaches of naïve Bayes tree, alternating decision tree, and random forest methods. (83 citations)
- COVID-19 Detection through Transfer Learning Using Multimodal Imaging Data (33 citations)
In his most recent research, the most cited papers focused on:
- Artificial intelligence
- Statistics
- Machine learning
The scientist’s investigation covers issues in Random forest, Landslide, Statistics, Analytic hierarchy process and Receiver operating characteristic.
The various areas that Biswajeet Pradhan examines in his Landslide study include Cartography, Spatial database, Data mining and Physical geography.
The Statistics study combines topics in areas such as Elevation, Ensemble forecasting and Flood myth.
His Analytic hierarchy process research includes elements of Multi criteria decision, Landslide susceptibility, Natural disaster and Environmental resource management.
The study incorporates disciplines such as Decision tree, Statistic, Gully erosion and Mean squared error in addition to Receiver operating characteristic.
His study looks at the relationship between Hydrology and topics such as Agricultural land, which overlap with Geographic information system.
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