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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)

Carboxymethyl starch cross-linked by electron beam radiation in presence of acrylic acid sensitizer

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Nuclear Science and Techniques 2013年第B12期24卷 19-22页

作者： doan binh Nguyen Thanh Duoc Pham Thi Thu Hong R & D Center for Radiation Technology Vietnam Atomic Energy Institute 202A St. 11 Linh Xuan Ward Thu Duc District Ho Chi Minh City Vietnam

Carboxymethyl starch (CMS) can be cross-linked by electron beam radiation to form a biocompatible and environment-friendly hydrogel at a high absorbed dose and a condensed CMS concentration. Acrylic acid (AAc) can be used as a sensitizer in order to reduce the absorbed doses to an acceptable certain level. At an absorbed dose of 3-4 kGy, the gel content of crosslinked CMS can be obtained about 50% with 5% (w/w) AAc concentration used. The compressive strength of CMS samples increased with increasing their cross-linked densities due to raising absorbed doses. The swelling ratio of cross-linked CMS was also attainable at a maximum of 50 times in the distilled water. The enzymatic degradation of cross-linked CMS was carried out in acetate buffer pH 4.6 with 0.1% α-amylase enzymatic solution incubated at 40°C for 6 h. The crosslinked CMS samples were degraded slower than uncrosslinked CMS ones. The results indicated that the highly cross-linked CMS was almost fully degradable when the enzymatic hydrolysis was performed during 6 h. The FT IR spectra of cross-linked CMS in the presence of AAc were examined to observe the carboxyl group of AAc in the structure of cross-linked CMS. The hydrophilic of cross-linked CMS surface was determined by a contact-angle analysis. © 2013, Science Press. All rights reserved.

关键词：交联密度羧甲基淀粉电子束辐射丙烯酸敏化剂 FT-IR光谱吸收剂量 CMS

On the System Performance of Mobile Edge Computing in an Uplink NOMA WSN With a Multiantenna Access Point Over Nakagami-m Fading

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IEEE/CAA Journal of Automatica Sinica 2022年第4期9卷 668-685页

作者： van-Truong Truong van Nhan Vo Dac-binh Ha Chakchai So-In the Faculty of Electrical-Electronic Engineering Duy Tan University the Institute of Research and Development Duy Tan University the Faculty of Information Technology Duy Tan University IEEE the Applied Network Technology(ANT)Laboratory Department of Computer ScienceCollege of ComputingKhon Kaen University

In this paper,we study the system performance of mobile edge computing(MEC)wireless sensor networks(WSNs)using a multiantenna access point(AP)and two sensor clusters based on uplink nonorthogonal multiple access(NOMA).Due to limited computation and energy resources,the cluster heads(CHs)offload their tasks to a multiantenna AP over Nakagami-m *** proposed a combination protocol for NOMA-MEC-WSNs in which the AP selects either selection combining(SC)or maximal ratio combining(MRC)and each cluster selects a CH to participate in the communication process by employing the sensor node(SN)*** derive the closed-form exact expressions of the successful computation probability(SCP)to evaluate the system performance with the latency and energy consumption constraints of the considered *** results are provided to gain insight into the system performance in terms of the SCP based on system parameters such as the number of AP antennas,number of SNs in each cluster,task length,working frequency,offloading ratio,and transmit power ***,to determine the optimal resource parameters,i.e.,the offloading ratio,power allocation of the two CHs,and MEC AP resources,we proposed two algorithms to achieve the best system *** approach reveals that the optimal parameters with different schemes significantly improve SCP compared to other similar *** use Monte Carlo simulations to confirm the validity of our analysis.

关键词： Mobile edge computing(MEC) Nakagami-m fading offloading selection combining(SC)/maximal ratio combining(MRC) successful computation probability(SCP) uplink nonortho-gonal multiple access(NOMA) wireless sensor networks(WSNs)

An advection fog event response to future climate forcing in the 2030s-2080s:a case study for Shanghai

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Frontiers of Earth Science 2023年第2期17卷 527-546页

作者： Ying GU Hiroyuki KUSAKA Quang-van doan School of Air Transportation Shanghai University of Engineering ScienceShanghai 201620China Center for Computational Sciences University of Tsukuba1-1-1 TennodaiTsukubaIbaraki 305-8577Japan

Fog may continue to inhibit industry in the ***,we focused on a specific advection fog event in Shanghai,China,and applied a pseudo global warming method to examine advection fog under the RCP8.5 highemission *** method involved downscaling the future atmospheric conditions over the ensemble average of 19 global climate models from the fifth phase of the Coupled Model Intercomparison Project(CMIP5).We used the Weather Research and Forecasting Model coupled with a single-layer urban canopy model(WRF‒UCM)to run four sensitivity experiments and examined the advection fog and its relationship to changes in meteorological *** results showed that:1)The advection fog event tended to remain in Shanghai despite global warming;2)advection fog will not change greatly in the future;however,the onset and dissipation times will change slightly;3)relative humidity(RH)locally increases prior to the onset of the advection fog,and decreases at the dissipating stage,despite the current and future experiments having the same RH initial and boundary conditions;4)a small increase in surface air temperature and an increase in RH contribute to the early advection fog onset,and vice *** facilitates the early onset and dissipation of advection fog.

关键词： advection fog global warming PGW DDS WRF-UCM Shanghai

Dam deformation analysis based on BPNN merging models

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Geo-Spatial Information Science 2018年第2期21卷 149-157页

作者： Jingui Zou Kien-Trinh Thi Bui Yangxuan Xiao Chinh van doan School of Geodesy and Geomatics Wuhan UniversityWuhanChina Geomatics Centre Thuyloi UniversityHanoiVietnam Institute of Technique Special Engineering Le Quy Don Technical UniversityHanoiVietnam

Hydropower has made a significant contribution to the economic development of Vietnam,thus it is important to monitor the safety of hydropower dams for the good of the country and the *** this paper,dam horizontal displacement is analyzed and then forecasted using three methods:the multi-regression model,the seasonal integrated auto-regressive moving average(SARIMA)model and the back-propagation neural network(BPNN)merging *** monitoring data of the Hoa binh Dam in Vietnam,including horizontal displacement,time,reservoir water level,and air temperature,are used for the *** results indicate that all of these three methods can approximately describe the trend of dam deformation despite their different forecast ***,their short-term forecasts can provide valuable references for the dam safety.

关键词： Dam deformation analysis multi-regression model Back-propagation Neural Network(BPNN) Seasonal Integrated Auto-regressive Moving Average(SARIMA)model merging model

Integrating Machine Learning and Evidential Reasoning for User Profiling and Recommendation

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Journal of Systems Science and Systems Engineering 2023年第4期32卷 393-412页

作者： Toan Nguyen Mau Quang-Hung Le Duc-Vinh Vo Duy doan van-Nam Huynh University of Information Technology Ho Chi Minh CityVietnam Vietnam National University Ho Chi Minh CityVietnam Department of Information Technology Quy Nhon UniversityQuy NhonVietnam Ho Chi Minh City University of Banking Ho Chi Minh CityVietnam School of Knowledge Science Japan Advanced Institute of Science and TechnologyIshikawaJapan

User profiles representing users’preferences and interests play an important role in many applications of personalized *** the rapid growth of social platforms,there is a critical need for efficient solutions to learn user profiles from the information they shared on social platforms so as to improve the quality of recommendation *** problem of user profile learning is significantly challenging due to difficulty in handling data from multiple sources,in different formats and often associated with *** this paper,we introduce an integrated approach that combines advanced Machine Learning techniques with evidential reasoning based on Dempster-Shafer theory of evidence for user profiling and *** developed methods for user profile learning and multi-criteria collaborative filtering are demonstrated with experimental results and analysis that show the effectiveness and practicality of the integrated approach.A proposal for extending multi-criteria recommendation systems by incorporating user profiles learned from different sources of data into the recommendation process so as to provide better recommendation capabilities is also highlighted.

关键词： Machine learning Dempster-Shafer theory of evidence user profiles personalized recommendation preferences

Study of vertically ascending flight of a hawkmoth model

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Acta Mechanica Sinica 2020年第5期36卷 1031-1045,I0002页

作者： Anh Tuan Nguyen Vu Dan Thanh Le The Hung Tran V.N.Due van binh Phung Faculty of Aerospace Engineering Le Quy Don Technical UniversityHanoiVietnam Institute of Theoretical and Applied Research.Duy Tan University HanoiVietnam Division of Construction Computation Institute for Computational ScienceTon Due Thang UniversityHo Chi Minh CityVietnam Faculty of Civil Engineering Ton Due Thang UniversityHo Chi Minh CityVietnam

This paper provides insight into the wing kinematics,the power requirement and the dynamic stability characteristics of a hawkmoth model in vertically ascending *** wing kinematics of the hawkmoth model is obtained based on the minimum required power *** optimization process is conducted using genetic and simplex algorithms that are coupled with an artificial neural network to rapidly predict the aerodynamic force and required *** training data for the neural network are generated from an unsteady vortex-lattice *** to hover,the results in this study show the larger flapping frequency and the smaller rotation amplitude of the hawkmoth wing kinematics in ascending ***,more power is required when the ascending speed *** conducting a dynamic modal analysis based on a cycle-average approach,the certain effect of the ascending speed on the modal structures of the hawkmoth model was observed.

关键词： Hawkmoth Ascending flapping flight-Genetic algorithm Artificial neural network Flight dynamic stability

Behavior of noncircular tunnels excavated in stratified rock masses-Case of underground coal mines

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Journal of Rock Mechanics and Geotechnical Engineering 2019年第1期11卷 99-110页

作者： Ngoc Anh Do Daniel Dias van Diep Dinh Tien Tung Tran van Canh Dao Viet doan Dao Phuc Nhan Nguyen Department of Underground and Mining Construction.Faculty of Civil Engineering Hanoi University of Mining and Ceology School of Automotive and Transportation Engineering Hefei University of Technology Laboratory 35R Crenoble Alpes University

The amount of tunnels excavated along stratified/sedimentary rock masses in Quangninh coal mine area,Vietnam, is gradually increasing. Rock mass in Quangninh is characterized by beddings between rock layers. The behavior of stratified rock masses surrounding the tunnels depends on both the intact rock and the beddings between rock layers. The main characteristics of stratified rock masses that need to be considered are their heterogeneity and anisotropy. Depending on the dip angle of rock layers, movements and failure zones developed surrounding the tunnels can be asymmetrical over the vertical axis of tunnel. This asymmetry causes adverse behaviors of the tunnel structures. The objective of this study is to highlight convergences and yielded zones developed in rock masses surrounding noncircular tunnels in Quangninh coal mine area using a finite element method. The presence of bedding joints is explicitly simulated. The numerical results indicated that with the increase in dip angle of bedding joints, the stress asymmetry over the tunnel vertical axis increases. It gradually leads to an asymmetry of the failure zone surrounding the tunnel. An increase of rock mass quality means a decrease of rock mass sensitivity to the discontinuities. In addition,a dip angle of the bedding joints of approximately 45° could be considered as the critical angle at which the rock mass mechanism changes between sliding and bending.

关键词： Tunnel Bedding Stratification Anisotropic Heterogeneity