Results 11 to 20 of about 661,969 (212)
Selecting the Best Image Pairs to Measure Slope Deformation
Sensors, 2020 Optical remote sensing images can be used to monitor slope deformation in mountain regions. Abundant optical sensors onboard various platforms were designed to provide increasingly high spatial–temporal resolution images at low cost; however, finding the
Wentao Yang
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Machine Learning and Knowledge Extraction, 2020 A Long Short Term Memory (LSTM) based sales model has been developed to forecast the global sales of hotel business of Travel Boutique Online Holidays (TBO Holidays). The LSTM model is a multivariate model; input to the model includes several independent
Shakti Goel, Rahul Bajpai
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Uncertainty Analysis of Neutron Diffusion Eigenvalue Problem Based on Reduced-order Model
Yuanzineng kexue jishu, 2023 In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model ...
In order to improve the efficiency of core physical uncertainty analysis based on sampling statistics, the proper orthogonal decomposition (POD) and Galerkin projection method were combined to study the application feasibility of reduced-order model based on POD-Galerkin method in core physical uncertainty analysis. The two-dimensional two group TWIGL benchmark question was taken as the research object, the key variation characteristics of the core flux distribution were extracted under the finite perturbation of the group constants of each material region, and the full-order neutron diffusion problem was projected on the variation characteristics to establish a reduced-order neutron diffusion model. The reduced-order model was used to replace the full-order model to carry out the uncertainty analysis of the group constants of the material region. The results show that the bias of the mathematical expectation of keff calculated by reduced-order and full-order models is close to 1 pcm. In addition, compared with the calculation time required for uncertainty analysis of full-order model, the analysis time of reduced-order model (including the calculation time of the full-order model required for the construction of reduced-order model) is only 11.48%, which greatly improves the efficiency of uncertainty analysis. The biases of mathematical expectation of keff calculated by reduced-order and full-order models based on Latin hypercube sampling and simple random sampling are less than 8 pcm, and under the same sample size, the bias from the Latin hypercube sampling result is smaller. From the TWIGL benchmark test results, under the same sample size, Latin hypercube sampling method is more recommended for POD-Galerkin reduced-order model.
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Uncertainty analysis of health damage of coal mine dust using the Monte Carlo method
矿业科学学报, 2017 In order to provide an accurate insight into the occupational health situation of coal miners, a health damage assessment model of coal mine dust was established applying the methods of health risk assessment and exposure parameters.The dust health risks
Tong Ruipeng +4 more
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Frontiers in Ecology and Evolution, 2022 Pollen accumulation rates (PAR, grains cm–2 year–1) have been shown to be a reliable but methodologically complex bioproxy for quantitative reconstruction of past tree abundance.
Clarke A. Knight +6 more
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Remote Sensing, 2014 This paper aims to retrieve temporal high-resolution LAI derived by fusing MOD15 products (1 km resolution), field-measured LAI and ASTER reflectance (15-m resolution).
Yonghua Qu, Wenchao Han, Mingguo Ma
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Aviation, 2020 The increase in the number of Unmanned Aerial Vehicles (UAVs) and Micro Air Vehicles (MAVs), which are used in a variety of applications has led to a surge in low Reynolds number aerodynamics research.
Ahmed Aboelezz +3 more
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Journal of Nuclear Engineering, 2021 The EBR-II benchmark, which was recently included in the International Handbook of Evaluated Reactor Physics Benchmark Experiments, served as a basis for assessing the performance of the SCALE code system for fast reactor analyses.
Friederike Bostelmann +2 more
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Uncertainty analysis onto models and emission scenarios of climate change for projection of the temperature, precipitation, and evapotranspiration in the Neyshabour area [PDF]
مخاطرات محیط طبیعی, 2018 Climate change is not only caused the rise in temperature but also changes in the global precipitation cycle, which leads to variation in spatial and temporal precipitation patterns. In this study, climate change impacts were investigated on temperature,
Mostafa Yaghoobzadeh +2 more
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Machines, 2023 The accuracy of uncertainty analysis in suspension systems is closely tied to the precision of the probability distribution of sprung mass. Consequently, traditional assumptions regarding the probability distribution fail to guarantee the accuracy of ...
Cheng Li, Yuan Jing, Jinting Ni
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