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Salah Basem Ajjur and Emanuele Di Lorenzo
Natural groundwater recharge (GR) assessment depends on several hydrogeological and climatic inputs, where uncertainty is inevitable. Assessing how inputs? uncertainty affects GR estimation is important; however, it remains unclear in arid areas. This st...
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Han Lin Shang
A key summary statistic in a stationary functional time series is the long-run covariance function that measures serial dependence. It can be consistently estimated via a kernel sandwich estimator, which is the core of dynamic functional principal compon...
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Taehoon Lee, Byungjin Lee and Sangkyung Sung
This study proposes an enhanced integration algorithm that combines the magnetic field-based positioning system (MPS?Magnetic Pose Estimation System) with an inertial system with the advantage of an invariant filter structure. Specifically, to mitigate t...
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Minh-Quan Vo, Thu Nguyen, Michael A. Riegler and Hugo L. Hammer
Generative models have recently received a lot of attention. However, a challenge with such models is that it is usually not possible to compute the likelihood function, which makes parameter estimation or training of the models challenging. The most com...
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Lilai Jin, Sarah J. Higgins, James A. Thompson, Michael P. Strager, Sean E. Collins and Jason A. Hubbart
Saturated hydraulic conductivity (Ksat) is a hydrologic flux parameter commonly used to determine water movement through the saturated soil zone. Understanding the influences of land-use-specific Ksat on the model estimation error of water balance compon...
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Bomi Kim, Garim Lee, Yaewon Lee, Sohyun Kim and Seong Jin Noh
In this study, we analyzed the impact of model spatial resolution on streamflow predictions, focusing on high-resolution scenarios (<1 km) and flooding conditions at catchment scale. Simulation experiments were implemented for the Geumho River catchment ...
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Qian Cao, Jiashun Cao and Runze Xu
Low-impact development (LID) practices have been recognized as a promising strategy to control urban stormwater runoff and non-point source pollution in urban ecosystems. However, many experimental and modeling efforts are required to tailor an effective...
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Egor I. Chetkin, Sergei L. Shishkin and Bogdan L. Kozyrskiy
Bayesian neural networks (BNNs) are effective tools for a variety of tasks that allow for the estimation of the uncertainty of the model. As BNNs use prior constraints on parameters, they are better regularized and less prone to overfitting, which is a s...
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Xudong Han, Yongling Fu, Yan Wang, Mingkang Wang and Deming Zhu
The control accuracy and stability of the electrohydrostatic actuator (EHA) are directly impacted by parameter uncertainty, disturbance uncertainty, and non-matching disturbance, which negatively impacts aircraft rudder maneuvering performance and even r...
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Alessia Di Giovanni, Diego Di Curzio, Davide Pantanella, Cristiana Picchi and Sergio Rusi
Recently, new numerical methods have been applied to weather data for the estimation of water budget, especially when the lack of measured data is considerable. Geostatistics is one of the most powerful approaches when it comes to studying spatially rele...
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