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《化学科学与工程前沿(英文)》 2022年 第16卷 第4期 页码 523-535 doi: 10.1007/s11705-021-2083-5
关键词: solubility prediction machine learning artificial neural network random decision forests
ECOLOGICAL EFFECTS OF NITROGEN DEPOSITION ON URBAN FORESTS: AN OVERVIEW
《农业科学与工程前沿(英文)》 2022年 第9卷 第3期 页码 445-456 doi: 10.15302/J-FASE-2021429
● Patterns and effects of N deposition on urban forests are reviewed.
关键词: biodiversity carbon sequestration nitrogen deposition nutrient imbalance soil acidification urban forest
Simulation of heterogeneous two-phase media using random fields and level sets
George STEFANOU
《结构与土木工程前沿(英文)》 2015年 第9卷 第2期 页码 114-120 doi: 10.1007/s11709-014-0267-5
关键词: microstructure random fields level sets shape recovery two-phase media
Probabilistic analysis of secant piles with random geometric imperfections
《结构与土木工程前沿(英文)》 2021年 第15卷 第3期 页码 682-695 doi: 10.1007/s11709-021-0703-2
关键词: secant piles ultrasonic cross-hole testing probabilistic analysis reliability-based design random imperfections
Arash SEKHAVATIAN, Asskar Janalizadeh CHOOBBASTI
《结构与土木工程前沿(英文)》 2019年 第13卷 第1期 页码 66-80 doi: 10.1007/s11709-018-0461-y
关键词: uncertainty reliability analysis deep excavations random set method finite difference method
Xi F. XU
《结构与土木工程前沿(英文)》 2015年 第9卷 第2期 页码 107-113 doi: 10.1007/s11709-014-0268-4
关键词: multiscale finite element settlement perturbation random field geotechnical
以旋涡塔阵建立速成及高效益的人工防护林带 化整片沙漠为大片绿地
严隽森
《中国工程科学》 2003年 第5卷 第5期 页码 24-30
改造沙漠、利用沙漠,必须在沙漠中建立多道防护林带,才可大力推展沙产业、改良沙漠环境、并逐步化整片沙漠为大片绿地。对此,目前世界各国均束手无策或认为不可能。文章建议以旋涡塔阵及流体力学中的旋涡破裂特性及与镇定仓等的相互干扰,将塔阵后方的强风变为湍流弱风,而建立速成及高效益的人工防护林带;适当的重量分布在各镇定仓内,可使旋涡塔阵在狂风中仍屹立不移,在弱风区中,可大力推展沙产业,并与多方面的专家合力,适度开发利用沙漠;化整片沙漠为大片绿地,化荒芜及有严重危害的沙漠为宝地,并可在沙漠中以旋涡塔阵,保护长期及深层探勘的工作区,以利于发现及测定深埋地下的世界级的矿藏。
Named entity recognition for Chinese construction documents based on conditional random field
《工程管理前沿(英文)》 2023年 第10卷 第2期 页码 237-249 doi: 10.1007/s42524-021-0179-8
Bruno SUDRET,Hung Xuan DANG,Marc BERVEILLER,Asmahana ZEGHADI,Thierry YALAMAS
《结构与土木工程前沿(英文)》 2015年 第9卷 第2期 页码 121-140 doi: 10.1007/s11709-015-0290-1
关键词: polycrystalline aggregates crystal plasticity random fields spatial variability correlation structure
Nasser L. AZAD,Ahmad MOZAFFARI
《机械工程前沿(英文)》 2015年 第10卷 第4期 页码 405-412 doi: 10.1007/s11465-015-0354-x
The main scope of the current study is to develop a systematic stochastic model to capture the undesired uncertainty and random noises on the key parameters affecting the catalyst temperature over the coldstart operation of automotive engine systems. In the recent years, a number of articles have been published which aim at the modeling and analysis of automotive engines’ behavior during coldstart operations by using regression modeling methods. Regarding highly nonlinear and uncertain nature of the coldstart operation, calibration of the engine system’s variables, for instance the catalyst temperature, is deemed to be an intricate task, and it is unlikely to develop an exact physics-based nonlinear model. This encourages automotive engineers to take advantage of knowledge-based modeling tools and regression approaches. However, there exist rare reports which propose an efficient tool for coping with the uncertainty associated with the collected database. Here, the authors introduce a random noise to experimentally derived data and simulate an uncertain database as a representative of the engine system’s behavior over coldstart operations. Then, by using a Gaussian process regression machine (GPRM), a reliable model is used for the sake of analysis of the engine’s behavior. The simulation results attest the efficacy of GPRM for the considered case study. The research outcomes confirm that it is possible to develop a practical calibration tool which can be reliably used for modeling the catalyst temperature.
关键词: automotive engine calibration coldstart operation Gaussian process regression machine (GPRM) uncertainty and random noises
Crack propagation with different radius local random damage based on peridynamic theory
《结构与土木工程前沿(英文)》 2021年 第15卷 第5期 页码 1238-1248 doi: 10.1007/s11709-021-0695-y
Fault diagnosis of spur gearbox based on random forest and wavelet packet decomposition
Diego CABRERA,Fernando SANCHO,René-Vinicio SÁNCHEZ,Grover ZURITA,Mariela CERRADA,Chuan LI,Rafael E. VÁSQUEZ
《机械工程前沿(英文)》 2015年 第10卷 第3期 页码 277-286 doi: 10.1007/s11465-015-0348-8
This paper addresses the development of a random forest classifier for the multi-class fault diagnosis in spur gearboxes. The vibration signal’s condition parameters are first extracted by applying the wavelet packet decomposition with multiple mother wavelets, and the coefficients’ energy content for terminal nodes is used as the input feature for the classification problem. Then, a study through the parameters’ space to find the best values for the number of trees and the number of random features is performed. In this way, the best set of mother wavelets for the application is identified and the best features are selected through the internal ranking of the random forest classifier. The results show that the proposed method reached 98.68% in classification accuracy, and high efficiency and robustness in the models.
关键词: fault diagnosis spur gearbox wavelet packet decomposition random forest
Analytical method of capsizing probability in the time domain for ships in the random beam seas
LIU Liqin, TANG Yougang, LI Hongxia
《结构与土木工程前沿(英文)》 2007年 第1卷 第3期 页码 361-366 doi: 10.1007/s11709-007-0048-5
关键词: different survival probability different significant nonlinear differential narrowband
Tanvi SINGH, Mahesh PAL, V. K. ARORA
《结构与土木工程前沿(英文)》 2019年 第13卷 第3期 页码 674-685 doi: 10.1007/s11709-018-0505-3
关键词: batter piles oblique load test neural network M5 model tree random forest regression ANOVA
DUAN Wei
《能源前沿(英文)》 2008年 第2卷 第1期 页码 107-115 doi: 10.1007/s11708-008-0018-1
关键词: Probability sensitivity sensitivity analysis number cross-section statistical
标题 作者 时间 类型 操作
Machine learning-based solubility prediction and methodology evaluation of active pharmaceutical ingredients in industrial crystallization
期刊论文
Application of random set method in a deep excavation: based on a case study in Tehran cemented alluvium
Arash SEKHAVATIAN, Asskar Janalizadeh CHOOBBASTI
期刊论文
Multiscale stochastic finite element method on random field modeling of geotechnical problems – a fast
Xi F. XU
期刊论文
Characterization of random stress fields obtained from polycrystalline aggregate calculations using multi-scale
Bruno SUDRET,Hung Xuan DANG,Marc BERVEILLER,Asmahana ZEGHADI,Thierry YALAMAS
期刊论文
of catalyst temperature in automotive engines over coldstart operation in the presence of different random
Nasser L. AZAD,Ahmad MOZAFFARI
期刊论文
Fault diagnosis of spur gearbox based on random forest and wavelet packet decomposition
Diego CABRERA,Fernando SANCHO,René-Vinicio SÁNCHEZ,Grover ZURITA,Mariela CERRADA,Chuan LI,Rafael E. VÁSQUEZ
期刊论文
Analytical method of capsizing probability in the time domain for ships in the random beam seas
LIU Liqin, TANG Yougang, LI Hongxia
期刊论文
Modeling oblique load carrying capacity of batter pile groups using neural network, random forest regression
Tanvi SINGH, Mahesh PAL, V. K. ARORA
期刊论文