Institution
Hanoi University of Mining and Geology
Education•Hanoi, Vietnam•
About: Hanoi University of Mining and Geology is a education organization based out in Hanoi, Vietnam. It is known for research contribution in the topics: Coal mining & Artificial neural network. The organization has 600 authors who have published 781 publications receiving 12166 citations. The organization is also known as: HUMG.
Topics: Coal mining, Artificial neural network, Support vector machine, Zircon, Compressive strength
Papers published on a yearly basis
Papers
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TL;DR: This study introduces a framework for training and validation of shallow landslide susceptibility models by using the latest statistical methods and demonstrates the benefit of selecting the optimal machine learning techniques with proper conditioning selection method in shallow landslide susceptible mapping.
Abstract: Preparation of landslide susceptibility maps is considered as the first important step in landslide risk assessments, but these maps are accepted as an end product that can be used for land use planning. The main objective of this study is to explore some new state-of-the-art sophisticated machine learning techniques and introduce a framework for training and validation of shallow landslide susceptibility models by using the latest statistical methods. The Son La hydropower basin (Vietnam) was selected as a case study. First, a landslide inventory map was constructed using the historical landslide locations from two national projects in Vietnam. A total of 12 landslide conditioning factors were then constructed from various data sources. Landslide locations were randomly split into a ratio of 70:30 for training and validating the models. To choose the best subset of conditioning factors, predictive ability of the factors were assessed using the Information Gain Ratio with 10-fold cross-validation technique. Factors with null predictive ability were removed to optimize the models. Subsequently, five landslide models were built using support vector machines (SVM), multi-layer perceptron neural networks (MLP Neural Nets), radial basis function neural networks (RBF Neural Nets), kernel logistic regression (KLR), and logistic model trees (LMT). The resulting models were validated and compared using the receive operating characteristic (ROC), Kappa index, and several statistical evaluation measures. Additionally, Friedman and Wilcoxon signed-rank tests were applied to confirm significant statistical differences among the five machine learning models employed in this study. Overall, the MLP Neural Nets model has the highest prediction capability (90.2 %), followed by the SVM model (88.7 %) and the KLR model (87.9 %), the RBF Neural Nets model (87.1 %), and the LMT model (86.1 %). Results revealed that both the KLR and the LMT models showed promising methods for shallow landslide susceptibility mapping. The result from this study demonstrates the benefit of selecting the optimal machine learning techniques with proper conditioning selection method in shallow landslide susceptibility mapping.
861 citations
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TL;DR: In this paper, the mobilization of arsenic (As) to the groundwater was studied in a shallow Holocene aquifer on the Red River flood plain near Hanoi, Vietnam.
359 citations
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Tongji University1, University of Paris2, University of Kiel3, University of Hamburg4, Academia Sinica5, Chulalongkorn University6, National Cheng Kung University7, National Sun Yat-sen University8, University of the Philippines9, Hanoi University of Mining and Geology10, Universiti Malaysia Terengganu11, Indonesian Institute of Sciences12, Chinese Academy of Sciences13
TL;DR: In this paper, the authors synthesize existing clay mineralogical and geochemical data from similar to 1500 samples from the seafloor and surrounding rivers, deepwater mooring observation results, and high resolution glacial-cyclic clay mineralogy records from six high-quality sediment cores.
329 citations
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TL;DR: Evaluated and compared the results of evidential belief functions and fuzzy logic models for spatial prediction of landslide hazards in the Hoa Binh province of Vietnam, using geographic information systems show that all the models have good prediction capabilities.
Abstract: The main objective of this study is to evaluate and compare the results of evidential belief functions and fuzzy logic models for spatial prediction of landslide hazards in the Hoa Binh province of Vietnam, using geographic information systems. First, a landslide inventory map showing the locations of 118 landslides that have occurred during the last ten years was constructed using data from various sources. Then, the landslide inventory was randomly partitioned into training and validation datasets (70% of the known landslide locations were used for training and building the landslide models and the remaining 30% for the model validation). Secondly, nine landslide conditioning factors were selected (i.e., slope, aspect, relief amplitude, lithology, landuse, soil type, distance to roads, distance to rivers and distance to faults). Using these factors, landslide susceptibility index values were calculated using evidential belief functions and fuzzy logic models. Finally, landslide susceptibility maps were validated and compared using the validation dataset that was not used in the model building. The prediction-rate curves and area under the curves were calculated to assess prediction capability. The results show that all the models have good prediction capabilities. The model derived using evidential belief functions has the highest prediction capability. The model derived using fuzzy SUM has the lowest prediction capability. The fuzzy PRODUCT and fuzzy GAMMA models have almost the same prediction capabilities. In general, all the models yield reasonable results that may be used for preliminary landuse planning purposes.
323 citations
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TL;DR: The proposed PSO-NF model is a valid alternative tool that should be considered for tropical forest fire susceptibility modeling and is useful for forest planning and management in forest fire prone areas.
259 citations
Authors
Showing all 615 results
Name | H-index | Papers | Citations |
---|---|---|---|
Dieu Tien Bui | 70 | 260 | 14923 |
Christian Blodau | 40 | 94 | 5470 |
Hoang Nguyen | 35 | 148 | 3521 |
Xuan-Nam Bui | 23 | 82 | 1574 |
Duy Nguyen | 22 | 103 | 1803 |
Nguyen Thi Hue | 17 | 42 | 1074 |
Cuong Duong-Viet | 16 | 28 | 656 |
Viet-Ha Nhu | 15 | 29 | 704 |
Ngoc-Anh Do | 14 | 39 | 758 |
Phuong Thao Thi Ngo | 14 | 39 | 791 |
Dang Van Soa | 13 | 48 | 613 |
VanDung Nguyen | 13 | 65 | 544 |
Nam-Phong Nguyen | 13 | 36 | 508 |
Nguyen Van Minh | 12 | 58 | 698 |
Kennedy C. Onyelowe | 12 | 79 | 518 |