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Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 467-500页

作者： Landslide Susceptibility Mapping Using RBFN-Based Ensemble Machine Learning Models Duc-Dam Nguyen Nguyen viet Tiep Quynh-anh Thi Bui Hiep Van Le Indra Prakash Romulus Costache Manish Pandey Binh Thai Pham Faculty of Civil Engineering University of Transport TechnologyThanh XuanHa Noi100000Vietnam Faculty of Hydraulic Engineering Hanoi University of Civil EngineeringHa Noi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India Research Institute of the University of Bucharest Bucharest050663Romania National Institute of Hydrology and Water Management Bucharest013686Romania Department of Civil Engineering Transilvania University of BrasovBrasov500152Romania Danube Delta National Institute for Research and Development Tulcea820112Romania Marwadi University Research Center(MURC) Marwadi UniversityRajkotGujaratBharat360003India Department of Civil Engineering Faculty of Engineering&TechnologyMarwadi UniversityRajkotGujaratBharat360003India

This study was aimed to prepare landslide susceptibility maps for the Pithoragarh district in Uttarakhand,India,using advanced ensemble models that combined Radial Basis Function Networks(RBFN)with three ensemble learning techniques:DAGGING(DG),MULTIBOOST(MB),and ADABOOST(AB).This combination resulted in three distinct ensemble models:DG-RBFN,MB-RBFN,and ***,a traditional weighted method,Information Value(IV),and a benchmark machine learning(ML)model,Multilayer Perceptron Neural Network(MLP),were employed for comparison and *** models were developed using ten landslide conditioning factors,which included slope,aspect,elevation,curvature,land cover,geomorphology,overburden depth,lithology,distance to rivers and distance to *** factors were instrumental in predicting the output variable,which was the probability of landslide *** analysis of the models’performance indicated that the DG-RBFN model,with an Area Under ROC Curve(AUC)of 0.931,outperformed the other *** AB-RBFN model achieved an AUC of 0.929,the MB-RBFN model had an AUC of 0.913,and the MLP model recorded an AUC of *** results suggest that the advanced ensemble ML model DG-RBFN was more accurate than traditional statistical model,single MLP model,and other ensemble models in preparing trustworthy landslide susceptibility maps,thereby enhancing land use planning and decision-making.

关键词： Landslide susceptibility map spatial analysis ensemble modelling information values(IV)

Autohydrolysis treatment of bamboo and potassium oxalate(K_(2)C_(2)O_(4))activation of bamboo product for CO_(2) capture utilization

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Frontiers of Chemical Science and Engineering 2024年第4期18卷 63-72页

作者： Dang Duc viet Doan Thi Thao Khuong Duy anh Toshiki Tsubota Department of Materials Science Faculty of EngineeringKyushu Institute of TechnologyFukuoka 804-8550Japan vietnamese Academy of Forest Sciences Hanoi 10000Vietnam Collaborative Research Centre for Green Materials on Environmental Technology Kyushu Institute of TechnologyFukuoka 808-0196Japan

Typically,the hydroxide agents,such as sodium hydroxide and potassium hydroxide,which have corrosive properties,are used in the carbon activation *** this study,potassium oxalate(K_(2)C_(2)O_(4)),a less toxic and non-corrosive activating reagent,was used to synthesize activated carbon from the solid residue after autohydrolysis *** effect of the autohydrolysis treatment and the ratio of the K_(2)C_(2)O_(4)/solid residue are presented in this ***,the comparison between the activated carbon from bamboo and biochar from the solid residue are also *** resulting activated carbon from the solid residue exhibited a high surface area of up to 1432 m^(2)·g^(-1) and a total pore volume of up to 0.88 cm^(3)·g^(-1).The autohydrolysis treatment enhanced the microporosity properties compared to those without pretreatment of the activated *** microporosity of the activated carbon from the solid residue was dominated by the pore width at 0.7 nm,which is excellent for CO_(2) *** 25℃ and 1.013×10^(5) Pa,the CO_(2) captured reached up to 4.1 mmol·g^(-1).On the other hand,the ratio between K_(2)C_(2)O_(4) and the solid residue has not played a critical role in determining the porosity *** ratio of the K_(2)C_(2)O_(4)/solid residue of 2 could help the carbon material reach a highly microporous textural property that produces a high carbon capture *** finding proved the benefit of using the solid residue from the autohydrolysis treatment as a precursor material and offering a more friendly and sustainable activation carbon process.

关键词： activated carbon bamboo biochar CO_(2)capture potassium oxalate

A Method of Integrating Length Constraints into Encoder-Decoder Transformer for Abstractive Text Summarization

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Intelligent Automation & Soft Computing 2023年第10期38卷 1-18页

作者： Ngoc-Khuong Nguyen Dac-Nhuong Le viet-ha Nguyen anh-Cuong Le Faculty of Information Technology Haiphong UniversityHaiphong180000Vietnam Faculty of Information Technology VNU University of Engineering and TechnologyHanoi10000Vietnam Natural Language Processing and Knowledge Discovery Laboratory Faculty of Information TechnologyTon Duc Thang UniversityHo Chi Minh CityVietnam

Text summarization aims to generate a concise version of the original *** longer the summary text is,themore detailed it will be fromthe original text,and this depends on the intended ***,the problem of generating summary texts with desired lengths is a vital task to put the research into *** solve this problem,in this paper,we propose a new method to integrate the desired length of the summarized text into the encoder-decoder model for the abstractive text summarization *** length parameter is integrated into the encoding phase at each self-attention step and the decoding process by preserving the remaining length for calculating headattention in the generation process and using it as length embeddings added to theword *** conducted experiments for the proposed model on the two data sets,Cable News Network(CNN)Daily and NEWSROOM,with different desired output *** obtained results show the proposed model’s effectiveness compared with related studies.

关键词： Length controllable abstractive text summarization length embedding

An Efficient Adaptive Hierarchical Sliding Mode Control Strategy Using Neural Networks for 3D Overhead Cranes

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International Journal of Automation and computing 2019年第5期16卷 614-627页

作者： viet-anh Le hai-Xuan Le Linh Nguyen Minh-Xuan Phan Department of Automatic Control Hanoi University of Science and TechnologyHanoi 10000Vietnam Centre for Autonomous Systems University of Technology SydneyNew South Wales 2007Australia

In this paper, a new adaptive hierarchical sliding mode control scheme for a 3D overhead crane system is proposed. A controller is first designed by the use of a hierarchical structure of two first-order sliding surfaces represented by two actuated and un-actuated subsystems in the bridge crane. Parameters of the controller are then intelligently estimated, where uncertain parameters due to disturbances in the 3D overhead crane dynamic model are proposed to be represented by radial basis function networks whose weights are derived from a Lyapunov function. The proposed approach allows the crane system to be robust under uncertainty conditions in which some uncertain and unknown parameters are highly difficult to determine. Moreover, stability of the sliding surfaces is proved to be guaranteed. Effectiveness of the proposed approach is then demonstrated by implementing the algorithm in both synthetic and reallife systems, where the results obtained by our method are highly promising.

关键词： 3D overhead crane adaptive control hierarchical sliding mode control neural network radial basis function

Improved knowledge-based neural network(KBNN)model for predicting spring-back angles in metal sheet bending

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International Journal of Modeling, Simulation, and Scientific Computing 2014年第2期5卷 65-91页

作者： Tinh Quoc Bui anh viet Tran Abid Ali Shah Department of Civil Engineering University of Siegen Paul-Bontz-Str.9-1157076 SiegenGermany School of Mechanical and Automotive Engineering University of Ulsan San 29Mugeo 2-dong NamguP.O.Box 18UlsanSouth Korea

We develop an efficiently improved knowledge-based neural network(KBNN)associated with optimization algorithms and finite element analysis(FEA)to accurately predict spring-back angles in metal sheet *** well-known V and U prevalent processes of bending are *** KBNN predictive results are based on the empirical model and artificial neural network(ANN)*** empirical model is constructed from the FEA results using response surface method,while the multilayer perceptron is employed to create the *** trained KBNN can accurately model the relation-ship between the spring-back angles and process *** obtained results are validated against other existing methods showing a high accuracy.

关键词： Metal sheet bending spring-back angles knowledge-based neural network genetic algorithm optimization algorithm

Intermetallic Evolution of Al–Si-Coated Hot Stamping Steel During Modified Electrically Assisted Rapid Heating

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Acta Metallurgica Sinica(English Letters) 2018年第12期31卷 1327-1333页

作者： Kieu-anh Dinh Sung-Tae Hong Tien viet Luu Moon-Jo Kim Heung Nam han School of Mechanical Engineering University of Ulsan Liquid Processing & Casting R&D Group Korea Institute of Industrial Technology Department of Materials Science and Engineering RIAMSeoul National University

Modified electrically assisted(EA) rapid heating of Al–Si-coated hot stamping steel is suggested, and the intermetallic evolution in the coating during heating is experimentally investigated. In the modified EA rapid heating, a continuous electric current for a suitable duration is applied to a specimen to heat it to a temperature slightly below the melting temperature of the coating. The temperature of the specimen is then kept constant for a specified dwell time. The result of the microstructural analysis shows that the modified EA rapid heating could effectively increase the thickness of the intermetallic layer between the coating and steel substrate much faster than conventional furnace heating and induction heating. The effectiveness of EA rapid heating may be due to the athermal effect of the electric current on the mobility of atoms, in addition to the well-known resistance heating effect. EA rapid heating also provides a technical advantage in that partial austenization can be easily achieved by properly placing the electrodes, as demonstrated in the present study.

关键词： Hot stamping Electrically assisted rapid heating Partial austenization Al–Si-coated hot stamping steel

STRONG CONVERGENCE OF AN INERTIAL EXTRAGRADIENT METHOD WITH AN ADAPTIVE NONDECREASING STEP SIZE FOR SOLVING VARIATIONAL INEQUALITIES

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Acta Mathematica Scientia 2022年第2期42卷 795-812页

作者： Nguyen Xuan LINH Duong viet THONG Prasit CHOLAMJIAK Pham anh TUAN Luong Van LONG Department of Mathematics Mathematics Falcuty of Information TechnologyNational University of Civil Engineering Division of Applied Mathematics Thu Dau Mot UniversityBinh Duong ProvinceVietnam School of Science University of PhayaoPhayao 56000Thailand Paculty of Mathematical Economics National Economics UniversityHanoi CityVietnam

In this work,we investigate a classical pseudomonotone and Lipschitz continuous variational inequality in the setting of Hilbert space,and present a projection-type approximation method for solving this *** method requires only to compute one projection onto the feasible set per iteration and without any linesearch procedure or additional projections as well as does not need to the prior knowledge of the Lipschitz constant and the sequentially weakly continuity of the variational inequality mapping.A strong convergence is established for the proposed method to a solution of a variational inequality problem under certain mild ***,we give some numerical experiments illustrating the performance of the proposed method for variational inequality problems.

关键词： Inertial method Tseng’s extragradient viscosity method variational inequality problem pseudomonotone mapping strong convergence

Development of a PARCS/Serpent model for neutronics analysis of the Dalat nuclear research reactor

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Nuclear Science and Techniques 2021年第2期32卷 32-44页

作者： viet-Phu Tran Kien-Cuong Nguyen Donny hartanto Hoai-Nam Tran Vinh Thanh Tran Van-Khanh Hoang Pham Nhu viet ha Institute for Nuclear Science and Technology(INST) Vietnam Atomic Energy Institute(VINATOM)179 Hoang Quoc Viet str.Cau Giay DistrictHanoi 100000Vietnam Nuclear Research Institute(NRI) Vietnam Atomic Energy Institute(VINATOM)01 Nguyen Tu LucDalatLamdong 670000Vietnam Department of Mechanical and Nuclear Engineering University of SharjahPO.BOX 27272SharjahUnited Arab Emirates Institute of Fundamental and Applied Sciences Duy Tan UniversityHo Chi Minh city 700000Vietnam Faculty of Natural Science Duy Tan UniversityDanang 550000Vietnam Nuclear Safety Division Technical Support Center for Radiation and Nuclear Safety and Emergency ResponseVietnam Agency for Radiation and Nuclear Safety(VARANS)113 Tran Duy Hung str.Cau Giay DistrictHanoi 100000Vietnam

Cross-sectional homogenization for full-core calculations of small and complex reactor configurations,such as research reactors,has been recently recognized as an interesting and challenging *** paper presents the development of a PARCS/Serpent model for the neutronics analysis of a research reactor type TRIGA Mark-II loaded with Russian VVR-M2 fuel(known as the Dalat Nuclear Research Reactor or DNRR).The full-scale DNRR model and a supercell model for a shim/safety rod and its surrounding fuel bundles with the Monte Carlo code Serpent 2 were proposed to generate homogenized fewgroup cross sections for full-core diffusion calculations with *** full-scale DNRR model with Serpent 2 was also utilized as a reference to verify the PARCS/Serpent *** of the effective neutron multiplication factors,radial and axial core power distributions,and control rod worths showed a generally good agreement between PARCS and Serpent *** addition,the discrepancies between the PARCS and Serpent 2 results are also ***,the results indicate the applicability of the PARCS/Serpent model for further steady state and transient analyses of the DNRR.

关键词： PARCS Serpent 2 Group constant DNRR

A tree-based intelligence ensemble approach for spatial prediction of potential groundwater

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International Journal of Digital Earth 2020年第12期13卷 1408-1429页

作者： Mohammadtaghi Avand Saeid Janizadeh Dieu Tien Bui viet Hoa Pham Phuong Thao T.Ngo viet-ha Nhu Faculty of Natural Resources and Marine Sciences Tarbiat Modares UniversityTehranIran Geographic Information Science Research Group Ton Duc Thang UniversityHo Chi Minh CityVietnam Faculty of Environment and Labour Safety Ton Duc Thang UniversityHo Chi Minh CityVietnam Ho Chi Minh City Institute of Resources Geography Vietnam Academy of Science and TechnologyHo Chi Minh CityVietnam Institute of Research and Development Duy Tan UniversityDa NangVietnam Department of Geological-Geotechnical Engineering Hanoi University of Mining and GeologyHanoiVietnam

The objective of this research is to propose and confirm a new machine learning approach of Best-First tree(BFtree),AdaBoost(AB),MultiBoosting(MB),and Bagging(Bag)ensembles for potential groundwater mapping and assessing role of influencing *** Yasuj-Dena area(Iran)is selected as a case *** this regard,a Yasuj-Dena database was established with 362 springs locations and 12 groundwater-influencing factors(slope,aspect,elevation,stream power index(SPI),length of slope(LS),topographic wetness index(TWI),topographic position index(TPI),land use,lithology,distance from fault,distance from river,and rainfall).The database was employed to train and validate the proposed groundwater *** area under the curve(AUC)and statistical metrics were employed to check and confirm the quality of the *** result shows that the BFTree-Bag model(AUC=0.810,kappa=0.495)has the highest prediction performance,followed by the BFTree-MB model(AUC=0.785,kappa=0.477),and the BFTree-MB model(AUC=0.745,kappa=0.422).Compared to the benchmark of Random Forests,the BFTree-Bag model performs better;therefore,we conclude that the BFtree-Bag is a new tool should be used for modeling of groundwater potential.

关键词： Environmental modeling groundwater potential GIS ensemble model decision tree