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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)

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

A hierarchical system to predict behavior of soil and cantilever sheet wall by data-driven models

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Frontiers of Structural and Civil Engineering 2022年第6期16卷 667-684页

作者： Nang duc bui Hieu Chi PHAN Tiep duc PHAM Ashutosh Sutra DHAR Institute of Techniques for Special Engineering Le Quy Don Technical UniversityHanoi 100000Vietnam Faculty of Engineering and Applied Science Memorial University of NewfoundlandSt.John’sNL A1B 3X5Canada

The study proposes a framework combining machine learning(ML)models into a logical hierarchical system which evaluates the stability of the sheet wall before other *** study uses the hardening soil(HS)model to develop a 200-sample finite element analysis(FEA)database,to develop the ML ***,a system containing three trained ML models is proposed to first predict the stability status(random forest classification,RFC)followed by 1)the cantilever top horizontal displacement of sheet wall(artificial neural network regression models,RANN1)and 2)vertical settlement of soil(RANN2).The uncertainty of this data-driven system is partially investigated by developing 1000 RFC models,based on the application of random sampling technique in the data splitting *** on the distribution of the evaluation metrics reveals negative skewed data toward the 1.0000 *** implies a high performance of RFC on the database with medians of accuracy,precision,and recall,on test set are 1.0000,1.0000,and 0.92857,*** regression ANN models have coefficient of determinations on test set,as high as 0.9521 for RANN1,and 0.9988 for RANN2,*** parametric study for these regressions is also provided to evaluate the relative insight influence of inputs to output.

关键词： finite element analysis cantilever sheet wall machine learning artificial neural network random forest

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

Identifying the impediments and enablers of ecohealth for a case study on health and environmental sanitation in Hà Nam, Vietnam

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Infectious Diseases of Poverty 2014年第1期3卷 325-337页

作者： Vi Nguyen Hung Nguyen-Viet phuc Pham-duc Craig Stephen Scott A McEwen Department of Population Medicine Ontario Veterinary CollegeUniversity of Guelph2509 Stewart Building(#45)Guelph N1G 2W1ONCanada Public Health Risk Sciences Division Laboratory for Foodborne ZoonosesPublic Health Agency of Canada160 Research LaneUnit 206GuelphON N1G 5B2Canada Center for Public Health and Ecosystem Research Hanoi School of Public Health(HSPH)138 Giang Vo StreetHanoiVietnam Swiss Tropical and Public Health Institute(Swiss TPH) and International Livestock Research Institute(ILRI)Socinstrasse 57CH-4002 BaselSwitzerland and HanoiVietnam Swiss Federal Institute of Aquatic Science and Technology(ESWAG) Sandec–Department of Water and Sanitation in Developing CountriesP.O.BoxCH-8600DübendorfSwitzerland Department of Ecosystem and Public Health Faculty of Veterinary MedicineUniversity of CalgaryTRW 2D263280 Hospital DriveNWCalgaryAlberta T2N 4Z6Canada Centre for Coastal Health 900 Fifth StreetNanaimoBritish Columbia V9R 5S5Canada

Background:To date,research has shown an increasing use of the term“ecohealth”in literature,but few researchers have explicitly described how it has been *** investigated a project on health and environmental sanitation(the conceptual framework of which included the pillars of ecohealth)to identify the impediments and enablers of ecohealth and investigate how it can move from concept to ***:A case study approach was *** interview questions were centred on the nature of interactions and the sharing of information between ***:The analysis identified nine impediments and 15 enablers of *** themes relating to impediments,in particular-integration is not clear,don’t understand,and limited participation-related more directly to the challenges in applying the ecohealth pillars of transdisciplinarity and *** themes relating to enablers-awareness and understanding,capacity development,and interactions-facilitated usage of the research *** extracting information on the environmental,social,economic,and health aspects of environmental sanitation,we found that the issue spanned multiple scales and ***:The challenge of how to integrate these aspects should be considered at the design stage and throughout the research *** recommend that ecohealth research teams include a self-investigation of their processes in order to facilitate a comparison of moving from concept to practice,which may offer insights into how to evaluate the process.

关键词： Ecohealth Evaluation Health Sanitation Case study Vietnam

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

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

Morphological Change in the Northern Red River Delta,Vietnam

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Journal of Ocean University of China 2018年第6期17卷 1272-1280页

作者： bui Vuong Van FAN Daidu NGUYEN Dac Ve TRAN Dinh Lan TRAN duc Thanh HOANG Van Long NGUYEN Thi hong Hanh Institute of Marine Environment and Resources Vietnam Academy of Science and TechnologyHaiphong 18000Vietnam State Key Laboratory of Marine Geology Tongji UniversityShanghai 200092China Hanoi University of Mining and Geology Hanoi 10000Vietnam Graduate University of Science and Technology Vietnam Academy of Science and TechnologyHanoi 10000Vietnam

Coastal erosion has become a worldwide concern, typically in the densely populated Asian mega-river deltas. Severe coastal erosion in the southern Red River Delta(RRD) has been intensively studied. Coastal morphological change in the northern RRD was examined in detail through DEM(Digital Elevation Model) analysis based on time series of bathymetrical maps(1965–2004) and Landsat images(1975–2015) in this study. The results show that the northern RRD is featured by rapid coastal accretion in the past few decades, although suspended sediment flux has dropped by roughly 60% after the completeness of Hoa Binh Dam(HBD) in 1988 and relative sea level rose at 1.9 mm yr^(-1). However, accretion at the outer part of subtidal shoals and platforms was observed to slow down quickly or even turned into erosion in the last two decades. The resuspended sediments from the erosion zone can be transported landward to replenish the inner coastal zone, keeping the latter accretion in the near future to compensate for the sediment discharge decrease from the river. However, this lag effect should be terminated soon if other adverse effects go worse, e.g., damming rivers, sea-level rising, strengthening storms, land reclamation and other poor-designed coastal engineering. Coastal planners and managers should pay full attention to these changes.

关键词： Morphological change DEM coastal erosion coastal engineering coastal management tide-dominated Red River Delta