What is he best known for?
The fields of study he is best known for:
- Statistics
- Artificial intelligence
- Machine learning
His primary scientific interests are in Landslide, Support vector machine, Receiver operating characteristic, Cartography and Decision tree.
His Landslide study incorporates themes from Artificial neural network, Artificial intelligence and Logistic regression.
He has included themes like Machine learning and Pattern recognition in his Artificial intelligence study.
His Support vector machine research includes themes of Elevation, Data mining and Hazard.
His studies in Cartography integrate themes in fields like Spatial prediction and Natural hazard.
His work deals with themes such as C4.5 algorithm, Field, Normalized Difference Vegetation Index and Topographic Wetness Index, which intersect with Decision tree.
His most cited work include:
- Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree (491 citations)
- Spatial prediction models for shallow landslide hazards: a comparative assessment of the efficacy of support vector machines, artificial neural networks, kernel logistic regression, and logistic model tree (491 citations)
- A comparative assessment of support vector regression, artificial neural networks, and random forests for predicting and mapping soil organic carbon stocks across an Afromontane landscape. (316 citations)
What are the main themes of his work throughout his whole career to date?
Dieu Tien Bui mainly focuses on Landslide, Artificial intelligence, Support vector machine, Machine learning and Artificial neural network.
His studies deal with areas such as Cartography, Decision tree, Data mining and Receiver operating characteristic as well as Landslide.
Dieu Tien Bui interconnects Spatial prediction and Natural hazard in the investigation of issues within Cartography.
When carried out as part of a general Artificial intelligence research project, his work on Random forest, Ensemble forecasting and Deep learning is frequently linked to work in Alternating decision tree, therefore connecting diverse disciplines of study.
His Support vector machine study combines topics in areas such as Logistic regression, Least squares, Normalized Difference Vegetation Index and Topographic Wetness Index.
His research integrates issues of Mean squared error and Metaheuristic in his study of Artificial neural network.
He most often published in these fields:
- Landslide (38.41%)
- Artificial intelligence (34.06%)
- Support vector machine (32.25%)
What were the highlights of his more recent work (between 2019-2021)?
- Artificial intelligence (34.06%)
- Machine learning (22.10%)
- Artificial neural network (20.29%)
In recent papers he was focusing on the following fields of study:
His primary areas of investigation include Artificial intelligence, Machine learning, Artificial neural network, Support vector machine and Data mining.
Dieu Tien Bui combines subjects such as Flood myth, Flash flood and Key with his study of Artificial intelligence.
Many of his research projects under Machine learning are closely connected to Alternating decision tree with Alternating decision tree, tying the diverse disciplines of science together.
His Artificial neural network study combines topics from a wide range of disciplines, such as Mean squared error and Metaheuristic.
As a member of one scientific family, Dieu Tien Bui mostly works in the field of Data mining, focusing on Receiver operating characteristic and, on occasion, Gully erosion, Naive Bayes classifier, Variables and Logistic model tree.
His research on Landslide focuses in particular on Landslide susceptibility.
Between 2019 and 2021, his most popular works were:
- Prediction of Blast-Induced Ground Vibration in an Open-Pit Mine by a Novel Hybrid Model Based on Clustering and Artificial Neural Network (80 citations)
- A novel deep learning neural network approach for predicting flash flood susceptibility: A case study at a high frequency tropical storm area. (75 citations)
- Improved landslide assessment using support vector machine with bagging, boosting, and stacking ensemble machine learning framework in a mountainous watershed, Japan (72 citations)
In his most recent research, the most cited papers focused on:
- Statistics
- Machine learning
- Artificial intelligence
Dieu Tien Bui focuses on Artificial intelligence, Data mining, Support vector machine, Machine learning and Mean squared error.
His work in the fields of Decision tree model overlaps with other areas such as Multivariate adaptive regression splines.
He has included themes like Artificial neural network, Rotation forest and Hazard in his Data mining study.
His studies in Support vector machine integrate themes in fields like Hybrid approach, Stability, Cluster analysis, Flood myth and Receiver operating characteristic.
His work on Random forest and Ensemble forecasting as part of general Machine learning study is frequently linked to Alternating decision tree, bridging the gap between disciplines.
His study focuses on the intersection of Random forest and fields such as Landslide with connections in the field of Geographic information system, Natural hazard and Algorithm.
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