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Valerii Kozlovskyi, Ivan Shvets, Yurii Lysetskyi, Mikolaj Karpinski, Aigul Shaikhanova and Gulmira Shangytbayeva
The classification of the natural and anthropogenic destabilizing factors of a telecommunications network as a complex system is presented herein. This research shows that to evaluate the parameters of a telecommunications network in the presence of dest...
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Krzysztof Drachal and Michal Pawlowski
This study firstly applied a Bayesian symbolic regression (BSR) to the forecasting of numerous commodities? prices (spot-based ones). Moreover, some features and an initial specification of the parameters of the BSR were analysed. The conventional approa...
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Jiangtao Chen, Jiao Zhao, Wei Xiao, Luogeng Lv, Wei Zhao and Xiaojun Wu
Given the randomness inherent in fluid dynamics problems and limitations in human cognition, Computational Fluid Dynamics (CFD) modeling and simulation are afflicted with non-negligible uncertainties, casting doubts on the credibility of CFD. Scientifica...
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Uxia Garcia-Luis, Alejandro M. Gomez-San-Juan, Fermin Navarro-Medina, Carlos Ulloa-Sande, Alfonso Yñigo-Rivera and Alba Eva Peláez-Santos
The integration of uncertainty analysis methodologies allows for improving design efficiency, particularly in the context of instruments that demand precise pointing accuracy, such as space telescopes. Focusing on the VINIS Earth observation telescope de...
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Luis Zuloaga-Rotta, Rubén Borja-Rosales, Mirko Jerber Rodríguez Mallma, David Mauricio and Nelson Maculan
The forecasting of presidential election results (PERs) is a very complex problem due to the diversity of electoral factors and the uncertainty involved. The use of a hybrid approach composed of techniques such as machine learning (ML) and Simulation in ...
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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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Z. Jason Hou, Nicholas D. Ward, Allison N. Myers-Pigg, Xinming Lin, Scott R. Waichler, Cora Wiese Moore, Matthew J. Norwood, Peter Regier and Steven B. Yabusaki
The influence of coastal ecosystems on global greenhouse gas (GHG) budgets and their response to increasing inundation and salinization remains poorly constrained. In this study, we have integrated an uncertainty quantification (UQ) and ensemble machine ...
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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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Muhammad Sulman, Simone Mancini and Rasul Niazmand Bilandi
Incorporating steps into a hull reduces the wetted surface, promoting improved hydrodynamic lift and reduced resistance at high speeds, provided that the step is designed appropriately. Traditional hydrodynamics studies rely on scaled model testing in to...
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Akram Seifi, Soudabeh Golestani Kermani, Amir Mosavi and Fatemeh Soroush
Quantitatively analyzing models? uncertainty is essential for agricultural models due to the effect of inputs parameters and processes on increasing models? uncertainties. The main aim of the current study was to explore the influence of input parameter ...
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