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Mingfeng Huang, Jianping Sun, Kang Cai and Qiang Li
Although widely used in various fields due to its powerful capability of signal processing, empirical mode decomposition has to decompose signals separately, which limits its application for multivariate data such as the structural monitoring data record...
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Hesheng Tang, Xueyuan Guo, Liyu Xie and Songtao Xue
The uncertainty in parameter estimation arises from structural systems? input and output measured errors and from structural model errors. An experimental verification of the shuffled complex evolution metropolis algorithm (SCEM-UA) for identifying the o...
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Carla Camargos, Stefan Julich, Tobias Houska, Martin Bach and Lutz Breuer
The widely used, partly-deterministic Soil and Water Assessment Tool (SWAT) requires a large amount of spatial input data, such as a digital elevation model (DEM), land use, and soil maps. Modelers make an effort to apply the most specific data possible ...
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Mark L. Schmelter, Peter Wilcock, Mevin Hooten and David K. Stevens
A Bayesian approach to sediment transport modeling can provide a strong basis for evaluating and propagating model uncertainty, which can be useful in transport applications. Previous work in developing and applying Bayesian sediment transport models use...
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Hana Sevcikova, Brice Nichols
Pág. 805 - 820
Using an integrated land use and travel model system implemented for the Puget Sound region in Washington state, a Bayesian Melding technique is applied to represent variations in land use outcomes, and is propagated into travel choices across a multi-ye...
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Liang Xue
With the development of in-situ monitoring techniques, the ensemble Kalman filter (EnKF) has become a popular data assimilation method due to its capability to jointly update model parameters and state variables in a sequential way, and to assess the unc...
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Florimond De Smedt, Prabin Kayastha and Megh Raj Dhital
Naïve Bayes classification is widely used for landslide susceptibility analysis, especially in the form of weights-of-evidence. However, when significant conditional dependence is present, the probabilities derived from weights-of-evidence are biased, re...
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Arman Kakaie, C. Guedes Soares, Ahmad Kamal Ariffin and Wonsiri Punurai
A fracture mechanics-based fatigue reliability analysis of a submarine pipeline is investigated using the Bayesian approach. The proposed framework enables the estimation of the reliability level of submarine pipelines based on limited experimental data....
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Jeonghoon Lee, Jeonghyeon Choi, Jiyu Seo, Jeongeun Won and Sangdan Kim
In the context of hydrological model calibration, observational data play a central role in refining and evaluating model performance and uncertainty. Among the critical factors, the length of the data records and the associated climatic conditions are p...
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Bo Liu, Peng Zhang, Shubo Wu, Yajie Zou, Linbo Li and Shuning Tang
Parking duration analysis is an important aspect of evaluating parking demand. Identifying accurate distribution characteristics of parking duration can not only enhance parking efficiency and parking facility planning, but also provide essential support...
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Faisal Baig, Mohsen Sherif and Muhammad Abrar Faiz
Mountainous watersheds have always been a challenge for modelers due to large variability and insufficient ground observations, which cause forcing data, model structure, and parameter uncertainty. This study employed Differential Evolution Adaptive Metr...
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Kristian Gundersen, Guttorm Alendal, Anna Oleynik and Nello Blaser
The world?s oceans are under stress from climate change, acidification and other human activities, and the UN has declared 2021?2030 as the decade for marine science. To monitor the marine waters, with the purpose of detecting discharges of tracers from ...
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Cássio G. Rampinelli, Ian Knack and Tyler Smith
Many hydrologic studies that are the basis for water resources planning and management rely on streamflow information. Calibration and use of hydrologic models to extend flow series based on rainfall data, perform flood frequency analysis, or develop flo...
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Wouter Jan Klerk, Timo Schweckendiek, Frank den Heijer and Matthijs Kok
One of the most rapidly emerging measures in infrastructure asset management is Structural Health Monitoring (SHM), which aims at reducing uncertainty in structural performance by using monitoring equipment. As earthen flood defence structures typically ...
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Jun Wang, Zhongmin Liang, Xiaolei Jiang, Binquan Li and Li Chen
Real-time correction models provide the possibility to reduce uncertainties in flood prediction. However, most traditional techniques cannot accurately capture many sources of uncertainty and provide a quantitative evaluation. To account for a wide varie...
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Mousong Wu, Per-Erik Jansson, Xiao Tan, Jingwei Wu, Jiesheng Huang
Pág. 1 - 17
Water and energy processes in frozen soils are important for better understanding hydrologic processes and water resources management in cold regions. To investigate the water and energy balance in seasonally frozen soils, CoupModel combined with the gen...
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Jun Wang, Zhongmin Liang, Xiaolei Jiang, Binquan Li, Li Chen
Pág. 1 - 16
Real-time correction models provide the possibility to reduce uncertainties in flood prediction. However, most traditional techniques cannot accurately capture many sources of uncertainty and provide a quantitative evaluation. To account for a wide varie...
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Francisca Lanai Ribeiro Torres, Luana Medeiros Marangon Lima, Michelle Simões Reboita, Anderson Rodrigo de Queiroz and José Wanderley Marangon Lima
Streamflow forecasting plays a crucial role in the operational planning of hydro-dominant power systems, providing valuable insights into future water inflows to reservoirs and hydropower plants. It relies on complex mathematical models, which, despite t...
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Christin Bobe, Daan Hanssens, Thomas Hermans and Ellen Van De Vijver
Often, multiple geophysical measurements are sensitive to the same subsurface parameters. In this case, joint inversions are mostly preferred over two (or more) separate inversions of the geophysical data sets due to the expected reduction of the non-uni...
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Elliot Pachniak, Yongzhen Fan, Wei Li and Knut Stamnes
The Ocean Color?Simultaneous Marine and Aerosol Retrieval Tool (OC-SMART) is a robust data processing platform utilizing scientific machine learning (SciML) in conjunction with comprehensive radiative transfer computations to provide accurate remote sens...
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