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Prediction of Shear Bond Strength of Asphalt Concrete Pavement Using Machine Learning Models and Grid Search Optimization Technique

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Computer Modeling in Engineering & Sciences 2025年第1期142卷 691-712页

作者： Quynh-Anh Thi bui Dam duc Nguyen Hiep Van Le Indra Prakash Binh Thai Pham Civil Engineering Department University of Transport Technology54 Trieu KhucThanh XuanHanoi100000Vietnam DDG(R)Geological Survey of India Gandhinagar382010India

Determination of Shear Bond strength(SBS)at interlayer of double-layer asphalt concrete is crucial in flexible pavement *** study used three Machine Learning(ML)models,including K-Nearest Neighbors(KNN),Extra Trees(ET),and Light Gradient Boosting Machine(LGBM),to predict SBS based on easily determinable input ***,the Grid Search technique was employed for hyper-parameter tuning of the ML models,and cross-validation and learning curve analysis were used for training the *** models were built on a database of 240 experimental results and three input variables:temperature,normal pressure,and tack coat *** validation was performed using three statistical criteria:the coefficient of determination(R2),the Root Mean Square Error(RMSE),and the mean absolute error(MAE).Additionally,SHAP analysis was also used to validate the importance of the input variables in the prediction of the *** show that these models accurately predict SBS,with LGBM providing outstanding ***(Shapley Additive explanation)analysis for LGBM indicates that temperature is the most influential factor on ***,the proposed ML models can quickly and accurately predict SBS between two layers of asphalt concrete,serving practical applications in flexible pavement structure design.

关键词： Shear bond asphalt pavement grid search optimization machine learning

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)

A comparative study of three different learning algorithms applied to ANFIS for predicting daily suspended sediment concentration

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International Journal of Sediment Research 2017年第3期32卷 340-350页

作者： Keivan Kaveh Minh duc bui Peter Rutschmann Department of hydraulic and water resource engineering/School of civil engineering Technische Universitt Mnchen (TUM)

The modeling and prediction of suspended sediment in a river are key elements in global water recourses and environment policy and management. In the present study, an Adaptive Neuro-Fuzzy Inference System model trained with the Levenberg-Marquardt learning algorithm is considered for time series modeling of suspended sediment concentration in a river. The model is trained and validated using daily river discharge and suspended sediment concentration data from the Schuylkill River in the United States. The results of the proposed method are evaluated and compared with similar networks trained with the common Hybrid and Back-Propagation algorithms, which are widely used in the literature for prediction of suspended sediment concentration. Obtained results demonstrate that models trained with the Hybrid and Levenberg-Marquardt algorithms are comparable in terms of prediction ***, the networks trained with the Levenberg-Marquardt algorithm perform better than those trained with the Hybrid approach.

关键词： Fuzzy Inference System Hybrid learning rule Levenberg-Marquardt algorithm Schuylkill river Suspended sediments

Detecting Tuberculosis from Vietnamese X-Ray Imaging Using Transfer Learning Approach

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Computers, Materials & Continua 2023年第3期74卷 5001-5016页

作者： Ha Manh Toan Lam Thanh Hien Ngo duc Vinh Do nang Toan Institute of Information Technology–Vietnam Academy of Science and Technology Hanoi10072Vietnam Lac Hong University Bien HoaDong Nai76120Vietnam Hanoi University of Industry Hanoi11915Vietnam

Deep learning created a sharp rise in the development of autonomous image recognition systems,especially in the case of the medical *** lung problems,tuberculosis,caused by a bacterium called Mycobacterium tuberculosis,is a dangerous disease because of its infection and *** an infected person coughs or sneezes,tiny droplets can bring pathogens to others through *** mainly damages the lungs,but it also affects any part of the ***,during the period of the COVID-19(coronavirus disease 2019)pandemic,the access to tuberculosis diagnosis and treatment has become more difficult,so early and simple detection of tuberculosis has been more and more *** our study,we focused on tuberculosis diagnosis by using the chestX-ray image,the essential input for the radiologist’s profession,and researched the effectiveness of the transfer learning approach in the case study of Vietnamese chest X-ray *** proposed four strategies to clarify our hypothesis in different ways of applying transfer learning and different training set *** also prepared a Vietnamese X-ray image dataset with the support of the VRPACS team to provide the basis for training and testing deep learning *** experiments were carried out by applying three different architectures,Alexnet,Resnet,and Densenet,on international,Vietnamese,and combined X-ray image *** training,all models were verified on a pure Vietnamese X-rays *** results show that transfer learning is suitable in the case study of Vietnamese chest X-ray images with high evaluating metrics in terms of AUC(Area under the Receiver Operating Characteristic Curve),sensitivity,specificity,and *** the best strategy,most of the scores were more than 0.93,and all AUCs were more than 0.98.

关键词： Tuberculosis diagnosis transfer learning Vietnamese chest X-ray

Adaptive Controller Design for Dynamic Maneuvers of High Speed Underwater Vehicles

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China Ocean Engineering 2022年第2期36卷 311-321页

作者： bui duc Hong PHUC Sam-Sang YOU Phuc Thinh DOAN Sang-Do LEE Department of Mechanical Engineering The University of TulsaTulsaOK 74104USA Division of Mechanical Engineering Korea Maritime and Ocean UniversityBusan 49112Republic of Korea Institute of Interdisciplinary Social Sciences Nguyen Tat Thanh UniversityHo Chi Minh CityVietnam Division of Navigation and Information System Mokpo National Maritime UniversityMokpoJeollanam-do 58628Republic of Korea

The control synthesis of the high-speed underwater vehicle faces many technical challenges due to its inherent structure and surrounding operational *** this paper,the dynamical behavior is firstly described through a bifurcation analysis to give some insights for robust control *** a novel adaptive fractional-order sliding mode controller(AFOSMC)is realized to effectively manipulate the supercavitating vehicle against payload changes,nonlinear planing force,and external *** fractional order(FO)calculus can offer more flexibility and more freedom for tuning active control synthesis than the integer-order *** addition,the adaptation law has been presented to directly handle the payload change *** stability of the controlled vehicle system is proven via Lyapunov stability ***,the dynamic performance of the proposed controller is verified through extensive simulation results,which demonstrate the control accuracy with faster responses compared with existing integer-order ***,the proposed fractional order controllers can provide higher performance than their integer order counterparts with control algorithms.

关键词： fractional order calculus supercavitating underwater vehicles planing force payload change adaptive sliding mode control

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Engine performance and combustion characteristics of a direct injection compression ignition engine fueled waste cooking oil synthetic diesel

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International Journal of Coal Science & Technology 2020年第3期7卷 560-570页

作者： Thanh Viet Nguyen Khanh duc Nguyen nang Xuan Ho Vinh Duy Nguyen Department of Internal Combustion Engine School of Transportation EngineeringHanoi University of Science and TechnologyHanoiViet Nam Faculty of Vehicle and Energy Engineering Phenikaa UniversityYen NghiaHa-Dong DistrictHanoiViet Nam

Biodiesels produced from various feedstocks have been considered as alternative fuels used in internal combustion engines without major *** research focuses on producing biodiesel from waste cooking oil(WCOSD)by the catalytic cracking method using MgO as the catalyst and comparing the engine operating characteristics of the test engine when using WCOSD and traditional diesel(CD)as test *** a result,the brake power of the test engine fueled WCOSD,and traditional diesel is ***,the engine fuel consumption in the case of using WCOSD is slight increases in some operating ***,the nitrogen oxides emissions of the test engine fueled WCOSD are higher than those of CD at all tested *** trend is opposite for hydrocarbon emission as the HC emission of the engine fueled by WCOSD reduces 26.3%on *** smoke emission of the test engine in case of using WCOSD is lower 17%on average than that of ***,the carbon monoxide emissions are lower at the low and medium loads and higher at the full *** results show that the new biodiesel has the same characteristics as those of commercial biodiesel and can be used as fuel for diesel engines.

关键词： Feedstock Waste cooking oil Engine characteristics Exhaust missions Ignition timing Fuel consumption

Occurrence of microcystins in water,sediment,and aquatic animals in Dau Tieng Reservoir,Vietnam

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Journal of Oceanology and Limnology 2024年第6期42卷 1751-1763页

作者： Thanh Luu PHAM Manh Ha bui Tan duc NGUYEN Thanh Son DAO Faculty of Environment and Labour Safety Ton Duc Thang UniversityHo Chi Minh City 700000Vietnam Faculty of Environment Saigon UniversityHo Chi Minh City 700000Vietnam Guangdong Provincial Key Laboratory of Marine Disaster Prediction and Prevention and Guangdong Provincial Key Laboratory of Marine BiotechnologyShantou UniversityShantou 515063China Faculty of Environment and Natural Resources Ho Chi Minh City University of Technology(HCMUT)Ho Chi Minh City 700000Vietnam Asian Center for Water Research(Centre Asiatique de Recherchesur l’Eau CARE)Ho Chi Minh City University of Technology(HCMUT)Vietnam National UniversityHo Chi Minh City 700000Vietnam

This study investigates the variations of microcystins(MCs)in water,cyanobacterial blooms,sediment,and aquatic organisms collected from the Dau Tieng Reservoir(DTR).*** liquid chromatography(HPLC)was employed to measure MC concentrations in various target *** indicate that Microcystis *** as the primary MC producer in the *** average concentrations of analyzed MCs in surface water ranged from 1.10 to 5.54μg/L,temporally and *** sediment,average concentrations varied from 0.15 to 1.13μg/g wet weight(WW)temporally and from 0.41 to 0.72μg/g WW *** were detected in different organs of fish species(Oreochromis *** Labiobarbus sp.)and in the entire soft tissues of bivalve(Corbicula sp.)and gastropod(Assiminea sp.).The highest observed MC concentration in July was 0.83±0.22μg/g WW in the intestines of fish Oreochromis *** presence of MCs in grass shrimp Palaemonetes *** observed solely in June,reaching a concentration of 0.28±0.19μg/g *** is the first report of MC accumulation in the grass shrimp Palaemonetes *** field *** the bivalve Corbicula sp.,the presence of analyzed MCs was consistent throughout the study period,except for March and September,with the highest concentrations in July at 0.77±0.1μg/g *** correlation analysis revealed significant positive correlations between MCs in water and sediment with MC concentrations in aquatic animals,indicating the potential transfer of MCs across different trophic *** estimated daily intake values for analyzed MCs indicate that fish collected from the DTR are considered safe for consumption,as long as only the edible organs,such as the muscle,are ***,bivalves or gastropods collected from the DTR are not safe for human *** study underscored the importance of monitoring MC accumulation in aquatic animals used as food to mitigate adverse effects on human health.

关键词： aquatic animal bioaccumulation cyanotoxin health risk toxic cyanobacteria

维普期刊数据库

Spatial prediction of rainfall-induced shallow landslides using hybrid integration approach of Least-Squares Support Vector Machines and differential evolution optimization:a case study in Central Vietnam

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International Journal of Digital Earth 2016年第11期9卷 1077-1097页

作者： Dieu Tien bui Binh Thai Pham Quoc Phi Nguyen Nhat-duc Hoang Geographic Information System Group Department of Business Administration and Computer ScienceUniversity College of Southeast NorwayBøi TelemarkNorway Faculty of Geomatics and Land Administration Hanoi University of Mining and GeologyHanoiVietnam Department of Civil Engineering Gujarat Technological UniversityAhmedabadGujaratIndia Department of Geotechnical Engineering University of Transport TechnologyHa NoiVietNam Department of Environmental Sciences Hanoi University of Mining and GeologyHanoiVietnam Faculty of Civil Engineering Institute of Research and DevelopmentDuy Tan UniversityDanangVietnam

This study represents a hybrid intelligence approach based on the differential evolution optimization and Least-Squares Support Vector Machines for shallow landslide prediction,named as *** LSSVM is used to establish a landslide prediction model whereas the DE is adopted to search the optimal tuning parameters of the LSSVM *** this research,a GIS database with 129 historical landslide records in the Quy Hop area(Central Vietnam)has been collected to establish the hybrid *** receiver operating characteristic(ROC)curve and area under the curve(AUC)were used to assess the performance of the newly constructed *** results show that the proposed model has high performances with approximately 82%of AUCs on both training and validating *** model’s results were compared with those obtained from other methods,Support Vector Machines,Multilayer Perceptron Neural Networks,and J48 Decision *** result comparison demonstrates that the DE-LSSVMSLP deems best suited for the dataset at hand;therefore,the proposed model can be a promising tool for spatial prediction of rainfall-induced shallow landslides for the study area.

关键词： Shallow landslide Least-Squares Support Vector Machines differential evolution GIS Vietnam

Dynamics modeling and motion control for high-speed underwater vehicles using H-infinity synthesis with anti-windup compensator

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Journal of Ocean Engineering and Science 2022年第1期7卷 84-91页

作者： Phuc duc Hong bui Sam-Sang You Hwan-Seong Kim Sang-Do Lee Department of Mechanical Engineering The University of TulsaTulsaOK 74104United States Division of Mechanical Engineering Korea Maritime and Ocean UniversityBusan 49112Republic of Korea Division of Logistics Engineering Korea Maritime and Ocean UniversityBusan 49112Republic of Korea Division of Navigation and Information System Mokpo National Maritime UniversityMokpoJeollanam-do 58628Republic of Korea

The control synthesis of a high-speed supercavitating vehicle(HSSV)faces many difficulties such as the stability,control,and maneuvering with dynamical uncertainties due to parameter perturbations,exter-nal disturbances,unmodeled dynamics,measurement noises,and actuator *** by the HSSV dynamical analysis,this paper proposes the H∞(i.e."H-infinity")robust control synthesis to gen-erate a robust low-order controller,which is intended for real implementations to ensure active control ***,the presented control scheme includes a feedback component and an anti-windup *** anti-windup synthesis is to provide system stability under actuator ***-tensive simulations show that the designed controller provides good performances with high robustness for vertical plane manoeuver while effectively eliminating planning forces,exogenous disturbances and noises as well as overcoming cavitator saturations.

关键词： Vehicle dynamics Planing force Vertical maneuver H-infinity control Anti-windup Actuator saturation