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Predicting soil erosion hazard in Lattakia Governorate(W Syria)

International Journal of Sediment Research 2021年第2期36卷 207-220页

作者： Mohammed Safwan Khallouf Alaa Alshiehabi Omran Bao pham Quoc Thi Thuy Linh Nguyen Nam Thai Van Tran Anh Duong Harsányi Endre Institution of Land Utilization Technology and Regional Planning Faculty of Agricultural and Food Sciences and Environmental Management University of Debrecen Administration of Natural Resources Management General Commission for Scientific Agricultural Research (GCSAR) 3. Department of Soil Sciences and Land Reclamation Faculty of Agriculture Al-Baath University Department of Soil and Environment Swedish University of Agricultural Sciences (SLU) Institute of Research and Development Duy Tan University Faculty of Environmental and Chemical Engineering Duy Tan University Faculty of Water Resource Engineering Thuyloi University Ho Chi Minh City University of Technology (HUTECH) Sustainable Management of Natural Resources and Environment Research Group Faculty of Environment and Labour Safety Ton Duc Thang University

The main objective of this study is to predict soil erosion in the Lattakia Governorate(W Syria) using the Water Erosion Prediction Project model(WEPP) and to compare the result with that of the RUSLE. Field survey and data collection were carried out, and 44 soil samples were analyzed. In addition, all the necessary input files were prepared for use in the WEPP model and RUSLE. Results show that more than of 80% of the locations studied experience slight to moderate erosion(less than 5 t/ha/y), whereas the rest of the locations experience severe soil erosion hazard. Moreover, the volume of runoff estimated by the WEPP model is in the range of 51 e321 mm, and the R~2 between the simulated soil erosion and the predicted runoff reached 0.68. Interestingly, the R~2 between the WEPP model and RUSLE is 0.56, which indicates a good correlation between the two models.

关键词： Soil erosion Run-off WEPP RUSLE Syria

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GIS-based landslide susceptibility modeling:A comparison between fuzzy multi-criteria and machine learning algorithms

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Geoscience Frontiers 2021年第2期12卷 857-876页

作者： Sk Ajim Ali Farhana Parvin Jana Vojteková Romulus Costache Nguyen Thi Thuy Linh Quoc Bao pham Matej Vojtek Ljubomir Gigović Ateeque Ahmad Mohammad Ali Ghorbani Department of Geography Faculty of ScienceAligarh Muslim University(AMU)AligarhUP 202002India Department of Geography and Regional Development Faculty of Natural SciencesConstantine the Philosopher University in NitraTrieda A.Hlinku 194901 NitraSlovakia Research Institute of the University of Bucharest 90-92 Sos.Panduri5th DistrictBucharest 050663Romania National Institute of Hydrology and Water Management București-Ploiești Road97E1st DistrictBucharest 013686Romania Thuyloi University 175 Tay SonDong DaHanoiViet Nam Institute of Research and Development Duy Tan UniversityDanang 550000Viet Nam Faculty of Environmental and Chemical Engineering Duy Tan UniversityDanang 550000Viet Nam Department of Geography University of Defence11000 BelgradeSerbia Sustainable Management of Natural Resources and Environment Research Group Faculty of Environment and Labour SafetyTon Duc Thang UniversityHo Chi Minh CityViet Nam

Hazards and disasters have always negative impacts on the way of *** is an overwhelming natural as well as man-made disaster that causes loss of natural resources and human properties throughout *** present study aimed to assess and compare the prediction efficiency of different models in landslide susceptibility in the Kysuca river basin,*** this regard,the fuzzy decision-making trial and evaluation laboratory combining with the analytic network process(FDEMATEL-ANP),Naïve Bayes(NB)classifier,and random forest(RF)classifier were ***,a landslide inventory map was produced with 2000 landslide and nonlandslide points by randomly dividedwith a ratio of 70%:30%for training and testing,*** geospatial database for assessing the landslide susceptibility was generated with the help of 16 landslide conditioning factors by allowing for topographical,hydrological,lithological,and land cover *** ReliefF methodwas considered for determining the significance of selected conditioning factors and inclusion in the model ***,the landslide susceptibility maps(LSMs)were generated using the FDEMATEL-ANP,Naïve Bayes(NB)classifier,and random forest(RF)classifier ***,the area under curve(AUC)and different arithmetic evaluation were used for validating and comparing the results and *** results revealed that random forest(RF)classifier is a promising and optimum model for landslide susceptibility in the study area with a very high value of area under curve(AUC=0.954),lower value of mean absolute error(MAE=0.1238)and root mean square error(RMSE=0.2555),and higher value of Kappa index(K=0.8435)and overall accuracy(OAC=92.2%).

关键词： Landslide susceptibility modeling Geographic information system Fuzzy DEMATEL Analytic network process Naïve Bayes classifier Random forest classifier

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上位效应对遗传算法可靠性的影响（英文）

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Journal of Zhejiang University-Science A(Applied Physics & Engineering) 2019年第2期20卷 109-116页

作者： Sajad JAFARI Tomasz KAPITANIAK Karthikeyan RAJAGOPAL Viet-Thanh pham Fawaz E.ALSAADI Biomedical Engineering Department Amirkabir University of Technology Division of Dynamics Lodz University of Technology Center for Nonlinear Dynamics Defence University6020 BishoftuEthiopia Modeling Evolutionary Algorithms Simulation and Artificial Intelligence Faculty of Electrical&Electronics EngineeringTon Duc Thang University Department of Information Technology Faculty of Computing and ITKing Abdulaziz University

目的:探讨遗传算法的局限性和实用性,并分析基于相互作用产生的上位效应对遗传算法可靠性的影响。创新点:1.指出遗传算法缺陷的根源;2.基于测试样本函数定义目标函数,以判断遗传算法的适用性。方法:1.基于非上位效应函数(表1)和上位效... 详细信息

目的:探讨遗传算法的局限性和实用性,并分析基于相互作用产生的上位效应对遗传算法可靠性的影响。创新点:1.指出遗传算法缺陷的根源;2.基于测试样本函数定义目标函数,以判断遗传算法的适用性。方法:1.基于非上位效应函数(表1)和上位效应函数(表2),以及非上位效应函数F4和上位效应函数F6的结构图来验证遗传算法可靠性;2.通过计算样本函数(公式(1))和遗传算法流程(图3)表达遗传算法的工作原理。3.利用克洛弗函数(公式(2))和计算不同结构角下的函数分布(图4),进一步判断匹配度(表3)和计算效率(表4);定义新的目标函数(公式(9))和一组新的变量(公式(10))来实现变量相关性解离。结论:1.对当前遗传算法存在的不足给出了独到见解,并认为正定性的假设并非可以保证遗传算法实际的有效性和优化性。2.定义成本代价函数用以判断遗传算法可靠性,并分别考虑上位性和非上位性效应两种情形。当成本代价函数在非上位性效应下时,遗传算法是有效的;否则,可以把N维函数降级为N个一维函数,从而采用更简单的算法来判断。基于一些通用的基准,进一步设计三类样本函数来证实以上判断,且这些样本函数适合于上位性效应情形和非上位效应情形。3.遗传算法的瓶颈在于主算子和相干匹配性;可以通过破坏某些结构来实现变量关系的解离,从而抑制相干匹配性对遗传算法的影响。希望相关读者在处理实际优化问题时能验证作者关于上位效应的定性结论,并给出更可靠的方法来表征这种效应。

关键词：上位性效应遗传算法相干匹配性叠加性优化成本代价函数

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Monitoring Heart Rate Variability Based on Self-powered ECG Sensor Tag

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Journal of Electronic & Information Systems 2022年第2期4卷 10-20页

作者： Nhat Minh Tran Ngoc-Giao pham thang Viet Tran Department of Telecommunication Sai Gon UniversityVietnam Department of Computing Fundamentals FPT UniversityHanoiVietnam Department of Science and Technology Nguyen Tat Thanh UniversityHo Chi Minh CityVietnam

This paper proposes a batteryless sensing and computational device to collect and process electrocardiography(ECG)signals for monitoring heart rate variability(HRV).The proposed system comprises of a passive UHF radio frequency identification(RFID)tag,an extreme low power microcontroller,a low-power ECG circuit,and a radio frequency(RF)energy *** microcontroller and ECG circuits consume less power of only~30μA and~3 mA,***,the proposed RF harvester operating at frequency band of 902 MHz~928 MHz can sufficiently collect available energy from the RFID reader to supply power to the system within a maximum distance of~2 *** extract R-peak of the ECG signal,a robust algorithm that consumes less time processing is also *** information of R-peaks is stored into an Electronic Product Code(EPC)Class 1st Generation 1st compliant ID of the tag and read by the *** reader is functioned to collected the R-peak data with sampling rate of 100ms;therefore,the user application can monitor fully range of *** performance of the proposed system shows that this study can provide a good solution in paving the way to new classes of healthcare applications.

关键词： Batteryless ECG sensor Heart rate monitoring UHF RFID

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Improved flood susceptibility mapping using a best first decision tree integrated with ensemble learning techniques

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Geoscience Frontiers 2021年第3期12卷 333-342页

作者： Binh Thai pham Abolfazl Jaafari Tran Van Phong Hoang Phan Hai Yen Tran Thi Tuyen Vu Van Luong Huu Duy Nguyen Hiep Van Le Loke Kok Foong University of Transport Technology Ha Noi 100000Viet Nam Research Institute of Forests and Rangelands Agricultural ResearchEducation and Extension Organization(AREEO)TehranIran Institute of Geological Sciences Vietnam Academy of Sciences and Technology84 Chua Lang StreetDong daHa NoiViet Nam Department of Geography School of Social EducationVinh UniversityViet Nam Department of Resource and Environment Management School of Agriculture and ResourcesVinh UniversityViet Nam Faculty of Geography VNU University of Science334 Nguyen TraiHa NoiViet Nam Institute of Research and Development Duy Tan UniversityDa Nang 550000Viet Nam Department for Management of Science and Technology Development Ton Duc Thang UniversityHo Chi Minh CityViet Nam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityViet Nam

Improving the accuracy of flood prediction and mapping is crucial for reducing damage resulting from flood *** this study,we proposed and validated three ensemble models based on the Best First Decision Tree(BFT)and the Bagging(Bagging-BFT),Decorate(Bagging-BFT),and Random Subspace(RSS-BFT)ensemble learning techniques for an improved prediction of flood susceptibility in a spatially-explicit manner.A total number of 126 historical flood events from the Nghe An Province(Vietnam)were connected to a set of 10 flood influencing factors(slope,elevation,aspect,curvature,river density,distance from rivers,flow direction,geology,soil,and land use)for generating the training and validation *** models were validated via several performance metrics that demonstrated the capability of all three ensemble models in elucidating the underlying pattern of flood occurrences within the research area and predicting the probability of future flood *** on the Area Under the receiver operating characteristic Curve(AUC),the ensemble Decorate-BFT model that achieved an AUC value of 0.989 was identified as the superior model over the RSS-BFT(AUC=0.982)and Bagging-BFT(AUC=0.967)models.A comparison between the performance of the models and the models previously reported in the literature confirmed that our ensemble models provided a reliable estimate of flood susceptibilities and their resulting susceptibility maps are trustful for flood early warning systems as well as development of mitigation plans.

关键词： Machine learning Ensemble learners Hybrid modeling

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巨峰和无核早红葡萄在越南谅山试种观察

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南方农业学报 2014年第7期45卷 1225-1229页

作者：黄江流 pham Thi thang 罗瑞鸿 NGUYN Thi Hà 吕荣华 LUONG Dǎng Ning CHU Vǎn DUòng NGUYN manh Tòng 彭宏祥 Ly Ming Nguyet LU'O'NG i Thuy CHU Xun Tien VI Vǎn Dúc NGUYN Duy Dng Ly Dúc Khiêm 熊俏广西农业科学院园艺研究所广西农业科学院葡萄与葡萄酒研究所广西农业科学院国际合作处南宁530007 越南谅山省科技厅越南谅山省科技厅科技进步应用中心

[目的]观察巨峰、无核早红葡萄在越南谅山省的引种表现,为其在越南推广种植提供参考依据.[方法]2009年春从中国南宁引入巨峰、无核早红两个鲜食葡萄品种在越南谅山省试种,调查其枝蔓生长量、物候期、果实性状、产量等相关指标.[结果]至... 详细信息

[目的]观察巨峰、无核早红葡萄在越南谅山省的引种表现,为其在越南推广种植提供参考依据.[方法]2009年春从中国南宁引入巨峰、无核早红两个鲜食葡萄品种在越南谅山省试种,调查其枝蔓生长量、物候期、果实性状、产量等相关指标.[结果]至第1年抚育冬季,巨峰葡萄枝蔓总长234.5 cm,上架茎粗0.84 cm;无核早红葡萄枝蔓总长294.1 cm,上架茎粗0.86 cm.在物候期方面,巨峰葡萄从萌芽至果实成熟需141～151 d,表现中熟;无核早红从萌芽至果实成熟需142～151 d,未表现其应有的早熟特性.在果实性状方面,巨峰葡萄2010～2012年3年平均单果重8.9 g,种子数1.04粒,可溶性固形物（TSS）含量17.5％;无核早红葡萄2010～2012年3年平均单果重6.8 g,TSS含量13.9％.在产量方面,巨峰葡萄2010～2012年产量分别为13.69、17.50和16.24 t/ha;无核早红葡萄2010～2012年产量分别为10.81、16.02和20.92t/ha.[结论]巨峰葡萄在越南谅山省种植表现丰产稳产优质,具有较好的适栽性,可大面积推广种植;无核早红葡萄表现丰产稳产,但表现低糖低酸,极易裂果,着色困难,不宜在越南大面积发展.

关键词：巨峰葡萄无核早红葡萄试种适栽性越南谅山省

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Ensemble machine learning models based on Reduced Error Pruning Tree for prediction of rainfall-induced landslides

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International Journal of Digital Earth 2021年第5期14卷 575-596页

作者： Binh Thai pham Abolfazl Jaafari Trung Nguyen-Thoi Tran Van Phong Huu Duy Nguyen Neelima Satyam Md Masroor Sufia Rehman Haroon Sajjad Mehebub Sahana Hiep Van Le Indra Prakash Division of Computational Mathematics and Engineering Institute for Computational ScienceTon Duc Thang UniversityHo Chi Minh CityViet Nam Faculty of Civil Engineering Ton Duc Thang UniversityHo Chi Minh CityViet Nam Research Institute of Forests and Rangelands Agricultural ResearchEducationand Extension Organization(AREEO)TehranIran Institute of Geological Sciences Vietnam Academy of Sciences and TechnologyHanoiViet Nam Faculty of Geography V.N.U.University of ScienceVietnam National UniversityHanoiViet Nam Discipline of Civil Engineering Indian Institute of Technology IndoreMadhya PradheshIndia Department of Geography Jamia Millia IslamiaNew DelhiIndia School of Environment Education and DevelopmentUniversity of ManchesterManchesterUK Institute of Research and Development Duy Tan UniversityDa NangViet Nam DDG(R)Geological Survey of India GujaratIndia

In this paper,we developed highly accurate ensemble machine learning models integrating Reduced Error Pruning Tree(REPT)as a base classifier with the Bagging(B),Decorate(D),and Random Subspace(RSS)ensemble learning techniques for spatial prediction of rainfallinduced landslides in the Uttarkashi district,located in the Himalayan range,*** do so,a total of 103 historical landslide events were linked to twelve conditioning factors for generating training and validation *** Mean Square Error(RMSE)and Area Under the receiver operating characteristic Curve(AUC)were used to evaluate the training and validation performances of the *** results showed that the single REPT model and its derived ensembles provided a satisfactory accuracy for the prediction of *** D-REPT model with RMSE=0.351 and AUC=0.907 was identified as the most accurate model,followed by RSS-REPT(RMSE=0.353 and AUC=0.898),B-REPT(RMSE=0.396 and AUC=0.876),and the single REPT model(RMSE=0.398 and AUC=0.836),*** prominent ensemble models proposed and verified in this study provide engineers and modelers with insights for development of more advanced predictive models for different landslide-susceptible areas around the world.

关键词： Machine learning ensemble modeling Bagging Decorate Random Subspace

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The Optimal Stopping Time for Selling an Asset When It Is Uncertain Whether the Price Process Is Increasing or Decreasing When the Horizon Is Infinite

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American Journal of Operations Research 2018年第2期8卷 82-91页

作者： Nguyen Khac Minh Nguyen Thanh Trung pham Van Khanh thang Long Institute of Mathematics and Applied Science Hanoi Vietnam Faculty of Fundamental Science Military Academy of Logistics Hanoi Vietnam

Assume that we want to shell an asset with unknown drift but known that the drift is a two value random variable, and the initial distribution can be estimated. As time goes by, this distribution is updated and base on the probability of the drift takes the small one gives us the stopping rule. Research results show that the optimal strategy to sell the asset is if the initial probability that the drift receives a small value greater than a certain threshold then liquidates the asset immediately, otherwise the asset holder will wait until the probability of the drift receives a small value passing a certain threshold, it is the optimal time to liquidate the asset.

关键词： Optimal Stopping Time Incomplete Information Probability Process

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Impacts of Exchange Rate Volatility and FDI on Technical Efficiency—A Case Study of Vietnamese Agricultural Sector

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American Journal of Operations Research 2015年第4期5卷 317-325页

作者： Nguyen Khac Minh pham Van Khanh Nguyen Viet Hung Economics and Management Faculty Thang Long University Hanoi Vietnam Institute of Economics and Corporate Group Hanoi Vietnam Faculty of Economics National Economics University Hanoi Vietnam

The objective of this research is to examine impacts of exchange rate volatility and FDI on efficiency of the Vietnamese agricultural sector at the provincial level for the period 1998-2011. Due to the characteristic of high uncertainty in agricultural production, the chance-constrained programming model would be used to estimate efficiency of the agricultural production sector. In order to study impacts of exchange rate volatility and FDI, we employ the two-stage model. In the first stage, we use the chance-constrained programming model to measure technical efficiency and ARIMA model to quantify exchange rate volatility. In the second stage, we use the fixed effect model to evaluate impacts of exchange rate volatility and FDI on efficiency of agricultural production in poor and rich provinces. The estimated results show that fluctuation in exchange rate volatility would reduce efficiency in agricultural production but FDI has an insignificant impact on the efficient production in Vietnam agricultural sector.

关键词： Chance-Constrained Programming DEA Exchange Rate Volatility FDI Technical Efficiency

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Super Efficiency and Misallocation: Evidence from Vietnamese Electric-Computer Industry

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American Journal of Operations Research 2018年第2期8卷 63-81页

作者： Nguyen Khac Minh pham Van Khanh Nguyen Thi Phuong thang Long Institute of Mathematics and Applied Science Hanoi Vietnam Faculty of Economics and Management Thang Long University Hanoi Vietnam

Misallocation means that the source is not distributed efficiently. This leads to an important question of how the relationship between misallocation and efficiency is (see [1]). The purpose of this study is to address the empirical relationship between misallocation and efficiency in the electric and computer industry in Vietnam during the 2005-2015 periods. To do this, we built a model that allowed us to evaluate the impact of misallocation and other factors on efficiency. The slack-based measured efficiency (SBM) model (Tone [2]), and the super-efficient model (Tone [3]) are used to estimate the firms’ efficiency. The approach of Hsieh and Klenow [4] is used to measure misallocation in the study area. Estimated results of the model about the relationship between misallocation and efficiency show that the variable representing the misallocation has a negative sign and statistical significance in all models. In other words, the misallocation negatively affects efficiency. The bigger the misallocation, the lower the efficiency.

关键词： Misallocation Super-Efficient Slack-Based Measured Efficiency

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