Results 41 to 50 of about 860,662 (182)
Stochastic Process and Simulation of Traction Load for High Speed Railways
IEEE Access, 2019 The traction load of a high-speed railway (HSR) may cause significant voltage fluctuations in the traction power supply system and the utility grid. To evaluate power quality, modeling traction load is an urgent need as well as a fundamental work.
Shaobing Yang, Kejian Song, Guangli Zhu
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Probabilistic Models for Competence Assessment in Education
Applied Sciences, 2022 Probabilistic models of competence assessment join the benefits of automation with human judgment. We start this paper by replicating two preexisting probabilistic models of peer assessment (PG1-bias and PAAS).
Alejandra López de Aberasturi Gómez +2 more
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An analytically solvable model of probabilistic network dynamics [PDF]
, 2005 We present a simple model of network dynamics that can be solved analytically for uniform networks. We obtain the dynamics of response of the system to perturbations. The analytical solution is an excellent approximation for random networks. A comparison
Bar-Yam, Yaneer +2 more
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Modelling Probabilistic Wireless Networks [PDF]
Logical Methods in Computer Science, 2013 We propose a process calculus to model high level wireless systems, where the topology of a network is described by a digraph. The calculus enjoys features which are proper of wireless networks, namely broadcast communication and probabilistic behaviour.
Cerone, Andrea, Hennessy, Matthew
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Denoising Diffusion Probabilistic Models for Probabilistic Energy Forecasting
2023 IEEE Belgrade PowerTech, 2023 Scenario-based probabilistic forecasts have become vital for decision-makers in handling intermittent renewable energies. This paper presents a recent promising deep learning generative approach called denoising diffusion probabilistic models. It is a class of latent variable models which have recently demonstrated impressive results in the computer ...
Capel, Esteban Hernandez +1 more
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Probabilistic Graphical Models [PDF]
, 2014 This report presents probabilistic graphical models that are based on imprecise probabilities using a simplified language. In particular the discussion is focused on credal networks and discrete domains. It describes the building blocks of credal networks algorithms to perform inference and discusses on complexity results and related work.
Antonucci, Alessandro +2 more
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On the Relevance of Using Bayesian Belief Networks in Wireless Sensor Networks Situation Recognition
Sensors, 2010 Achieving situation recognition in ubiquitous sensor networks (USNs) is an important issue that has been poorly addressed by both the research and practitioner communities.
Marco Zennaro +2 more
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An accurate model for SARS-CoV-2 pooled RT-PCR test errors
Royal Society Open Science, 2021 Pooling is a method of simultaneously testing multiple samples for the presence of pathogens. Pooling of SARS-CoV-2 tests is increasing in popularity, due to its high testing throughput.
Yair Daon, Amit Huppert, Uri Obolski
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Aggregating Reliable Submissions in Crowdsourcing Systems
IEEE Access, 2021 Crowdsourcing is a cost-effective method that gathers crowd wisdom to solve machine-hard problems. In crowdsourcing systems, requesters post tasks for obtaining reliable solutions.
Ayswarya R. Kurup +2 more
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RUDN Journal of Engineering Research, 2022 Phenomenological models represent the behavior of random phenomena in reality, the model and the function it should perform. Similarly, tuning parameters allow us to assess the fit of observed data to a variable in a particular mathematical model and to ...
Junior Orlando Mendoza Alava +4 more
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