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基于多变量概率模型的钻井周期预测方法

石油勘探与开发 2021年第4期48卷 851-860页

作者： luu quang hung LAU Man Fai NG Sebastian P.H. TING Clement P.W. WEE Reuben THEN Patrick H.H. 斯威本科技大学科学、工程与技术系澳大利亚霍桑3122 斯威本科技大学工程、计算与科学系马来西亚砂拉越93350 IDS公司马来西亚砂拉越93100

鉴于现有的预测钻井周期的方法忽视了影响钻井周期的关键因素因而精确度有限,提出采用多变量概率法预测钻井周期,并采用实测数据进行了算例分析和验证。利用自适应核密度估计法建立了各主要钻井阶段与深度相关的钻井周期概率模型,结合... 详细信息

鉴于现有的预测钻井周期的方法忽视了影响钻井周期的关键因素因而精确度有限,提出采用多变量概率法预测钻井周期,并采用实测数据进行了算例分析和验证。利用自适应核密度估计法建立了各主要钻井阶段与深度相关的钻井周期概率模型,结合蒙特卡洛模拟得出了一次完整钻井施工作业的总周期的概率分布。采用该方法对澳大利亚及亚洲地区192口井的钻井周期进行了预测。尽管现有数据记录不全,但经过统计分析发现,模型模拟结果与实测数据的匹配度很高。研究表明,在10%~90%的置信区间内,总钻井周期比无事故钻井周期延长至少4 d,至多12 d。采用该方法可以得到钻至一定深度的可能的施工周期,有利于评价整个钻井施工过程的风险,模拟数据还可以用于机器学习模型的训练。图10表2参34。

关键词：钻井周期多变量概率模型概率法马尔科夫链蒙特卡洛方法

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Simulation of stabilizing process of dielectric nanoparticle in optical trap using counter-propagating pulsed laser beams

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Chinese Optics Letters 2010年第3期8卷 332-334页

作者： Ho quang Quy Mai Van luu Hoang Dinh Hai Donan Zhuang Institute of Applied PhysicsNEWTECHPRO Vietnam Academy of Science and Technology Faculty of PhysicsVinh University Pedagogical College of Nghean Department of PhysicsKing Mingkut's University of Technology Thonburi

The stabilizing process of glass particle in water by optical trap using the pulsed counter-propagating Gaussian beams is investigated. The influence of the optical power and the particle dimension on the rate and tim... 详细信息

关键词： Simulation of stabilizing process of dielectric nanoparticle in optical trap using counter-propagating pulsed laser beams

A Deep Learning Based Approach for Context-Aware Multi-Criteria Recommender Systems

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Computer Systems Science & Engineering 2023年第1期44卷 471-483页

作者： Son-Lam VU quang-hung LE Faculty of Information Technology Quy Nhon UniversityQuy Nhon CityVietnam

Recommender systems are similar to an informationfiltering system that helps identify items that best satisfy the users’demands based on their pre-ference ***-aware recommender systems(CARSs)and multi-criteria recommender systems(MCRSs)are extensions of traditional recommender *** have integrated additional contextual information such as time,place,and so on for providing better ***,the majority of CARSs use ratings as a unique criterion for building ***,MCRSs utilize user preferences in multiple criteria to better generate *** to now,how to exploit context in MCRSs is still an open *** paper proposes a novel approach,which relies on deep learning for context-aware multi-criteria recommender *** apply deep neural network(DNN)mod-els to predict the context-aware multi-criteria ratings and learn the aggregation *** conduct experiments to evaluate the effect of this approach on the real-world dataset.A significant result is that our method outperforms other state-of-the-art methods for recommendation effectiveness.

关键词： Recommender systems context-aware multi-criteria deep learning deep neural network

Analysis of an Ar plasma jet in a dielectric barrier discharge conjugated with a microsecond pulse

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Plasma Science and Technology 2019年第9期21卷 73-81页

作者： Duc Ba NGUYEN quang hung TRINH Won Gyu LEE Young Sun MOK Department of Chemical and Biological Engineering Jeju National University Jeju 63243 Republic of Korea Center for Advanced Chemistry Institute of Research and Development Duy Tan University 03 Quang Trung Da Nang Vietnam Division of Chemical Engineering and Bioengineering Kangwon National University Chuncheon Kangwon 24341 Republic of Korea

In this work, an Ar plasma jet generated by an AC-microsecond-pulse-driven dielectric barrier discharge reactor, which had two ring-shaped electrodes isolated from the ambient atmosphere by transformer oil, was investigated. By special design of the oil insulation, a chemically active Ar plasma jet along with a safe and stable plasma process as well as low emission of CO and NOxwere successfully achieved. The results indicated that applied voltage and frequency were basic factors influencing the jet temperature, discharge power, and jet length, which increased significantly with the two operating parameters. Meanwhile, gas velocity affected the jet temperature in a reverse direction. In comparison with a He plasma jet, the Ar plasma jet had relatively low jet temperature under the same level of the input parameters, being preferable for bio-applications. The Ar plasma jet has been tested to interact with human skin within 5 min without the perception of burnt skin and electrical shock.

关键词： Ar plasma jet atmospheric pressure plasma jet OES of Ar gas emission of Ar plasma jet transformer oil

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

Oil and fatty acid accumulation during coriander (Coriandrum sativum L.) fruit ripening under organic cultivation

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The Crop Journal 2015年第4期3卷 366-369页

作者： quang-hung Nguyen Thierry Talou Mureil Cerny Philippe Evon Othmane Merah Université Fédérale de Toulouse Midi-Pyrénées INP-ENSIACET Laboratoire de Chimie Agro-industrielle Institut National de Recherche Agronomique UMR 1010 CAI

To evaluate the accumulation of oil and fatty acids in coriander during fruit ripening, a field experiment was conducted under organic cultivation conditions in Auch(near Toulouse,southwestern France) during the 2009 cropping season. The percentage and composition of the fatty acids of coriander were determined by gas chromatography. Our results showed that rapid oil accumulation started in early stages(two days after flowering, DAF). Twelve fatty acids were identified. Saturated and polyunsaturated acids were the dominant fatty acids at earlier stages(2–12 DAF), but decreased after this date. After this stage,petroselinic acid increased to its highest amount at 18 DAF. In contrast, palmitic acid followed the opposite trend. Saturated and polyunsaturated fatty acids decreased markedly and monounsaturated fatty acids increased during fruit maturation. It appears that the fruit of coriander may be harvested before full maturity.

关键词： Oil content Petroselinic acid Coriander Organic cultivation Fatty acid accumulation

Examining the nonlinear and threshold effects of the 5Ds built environment to land values using interpretable machine learning models

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Journal of Geographical Sciences 2024年第12期34卷 2509-2533页

作者： quang Cuong DOAN Khac hung VU Thi Kieu Trang TRINH Thi Cam Ngoc BUI Department of Urban Planning and Design The University of Hong KongHong KongChina Department of Land Management VNU University of ScienceHanoiVietnam Vietnam National University HanoiVietnam Faculty of Land Administration Hanoi University of Natural Resources and EnvironmentHanoiVietnam

Previous studies have extensively explored the critical influence of the built environment on land values,but the non-linear relationship has yet to be fully *** study aims to uncover the non-linear relationship between land values and the five built environment dimensions using machine learning algorithms and Shapley Additive ex Planation(SHAP).The results highlight that the Gradient Boost Decision Tree (GBDT) outperforms e Xtreme Gradient Boosting (XGBoost),Ordinary Least Squares (OLS),and Multiscale Geographically Weighted Regression (MGWR) in land value estimation,exhibiting higher R^(2) and lower Root Mean Square Error (RMSE) and Mean Absolute Error (MAE).The results illustrate that density and destination accessibility are the dominant factors,contributing 32.48%and37.38%to land value variation,*** observed that the top three factors affecting land values are the built-floor area ratio,the number of floors and the number of ***,the results revealed the non-linear relationship between the built environment and land values,suggesting that maintaining built environment features at optimal thresholds may increase land *** interaction effects may lead to bias in determining relationships between land values and the built *** study contributes to the literature by providing non-linear and threshold identification evidence in land value determinants,offering valuable insights for urban planners and real estate managers.

关键词： built environment land values housing price GBDT SHAP non-linear relationships machine learning

Machine learning based models for predicting compressive strength of geopolymer concrete

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Frontiers of Structural and Civil Engineering 2024年第7期18卷 1028-1049页

作者： quang-Huy LE Duy-hung NGUYEN Thanh SANG-TO Samir KHATIR Hoang LE-MINH Amir H.GANDOMI Thanh CUONG-LE Center for Engineering Application and Technology Solutions Ho Chi Minh City Open UniversityHo Chi Minh 700000Vietnam Institute of Civil Engineering Ho Chi Minh City University of TransportHo Chi Minh 700000Vietnam Faculty of Engineering&Information Technology University of Technology SydneyUltimoNSW 2007Australia

Recently,great attention has been paid to geopolymer concrete due to its advantageous mechanical and environmentally friendly *** effort has been made in experimental studies to advance the understanding of geopolymer concrete,in which compressive strength is one of the most important *** facilitate engineering work on the material,an efficient predicting model is *** this study,three machine learning(ML)-based models,namely deep neural network(DNN),K-nearest neighbors(KNN),and support vector machines(SVM),are developed for forecasting the compressive strength of the geopolymer concrete.A total of 375 experimental samples are collected from the literature to build a database for the development of the predicting models.A careful procedure for data preprocessing is implemented,by which outliers are examined and removed from the database and input variables are standardized before feeding to the fitting *** standard K-fold cross-validation approach is applied for evaluating the performance of the models so that overfitting status is well managed,thus the generalizability of the models is *** effectiveness of the models is assessed via statistical metrics including root mean squared error(RMSE),mean absolute error(MAE),correlation coefficient(R),and the recently proposed performance index(PI).The basic mean square error(MSE)is used as the loss function to be minimized during the model fitting *** three ML-based models are successfully developed for estimating the compressive strength,for which good correlations between the predicted and the true values are obtained for DNN,KNN,and *** numerical results suggest that the DNN model generally outperforms the other two models.

关键词： geopolymer concrete compressive strength prediction machine-learning based model deep neural network K-nearest neighbor support vector machines

First Records of Megophrys daweimontis Rao and Yang, 1997 and Amolops vitreus(Bain, Stuart and Orlov, 2006)(Anura: Megophryidae, Ranidae) from Vietnam

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Asian Herpetological Research 2015年第1期6卷 66-72页

作者： Dzung Trung LE Anh Van PHAM Son hung Lan NGUYEN Thomas ZIEGLER Truong quang NGUYEN Faculty of Biology Hanoi National University of Education Faculty of Biology and Chemistry Tay Bac University AG Zoologischer Garten Kln Institute of Ecology and Biological Resources Vietnam Academy of Science and Technology

Two amphibian species,Megophrys daweimontisandAmolops vitreus,are recorded for the ifrst time from Vietnam, on the basis of a new amphibian collection from Dien Bien and Son La provinces. In addition, acoustic analysis ofA. vitreus is also provided based on the advertisement calls recorded in Muong Nhe Nature Reserve of Dien Bien Province, Vietnam.

关键词： Amolops vitreus Megophrys daweimontis new records advertisement call Dien Bien Province Son La Province