Results 31 to 40 of about 25,679,411 (340)

Uncertainty Analysis of the Adequacy Assessment Model of a Distributed Generation System [PDF]

, 2012
Due to the inherent aleatory uncertainties in renewable generators, the reliability/adequacy assessments of distributed generation (DG) systems have been particularly focused on the probabilistic modeling of random behaviors, given sufficient informative
Li, Yanfu, Zio, Enrico
core   +3 more sources

Modeling Positional Uncertainty of Linear Features in Geographic Information Systems [PDF]

مجلة جامعة النجاح للأبحاث العلوم الطبيعية, 1997
This paper describes a probabilistic approach to model positional uncertainty of linear features in a vector-based geographic information system (GIS). Positional uncertainty is one of the components of uncertainty inherent in any object description in ...
Fayez Shaheen
doaj   +1 more source

Modeling Emergency Logistics Location-Allocation Problem with Uncertain Parameters

Systems, 2022
In order to model the emergency facility location-allocation problem with uncertain parameters, an uncertain multi-objective model is developed within the framework of uncertainty theory.
Hui Li, Bo Zhang, Xiangyu Ge
doaj   +1 more source

Bayesian Deep Convolutional Encoder-Decoder Networks for Surrogate Modeling and Uncertainty Quantification [PDF]

Journal of Computational Physics, 2018
We are interested in the development of surrogate models for uncertainty quantification and propagation in problems governed by stochastic PDEs using a deep convolutional encoder–decoder network in a similar fashion to approaches considered in deep ...
Yinhao Zhu, N. Zabaras
semanticscholar   +1 more source

Modeling Extragalactic Foregrounds and Secondaries for Unbiased Estimation of Cosmological Parameters From Primary CMB Anisotropy [PDF]

, 2011
Using the latest physical modeling and constrained by the most recent data, we develop a phenomenological parameterized model of the contributions to intensity and polarization maps at millimeter wavelengths from external galaxies and Sunyaev-Zeldovich ...
Amblard, Battaglia, Cardoso, Dunkley, Fendt, Fixsen, G. Holder, Giavalisco, Giodini, Gold, Gruzinov, Haiman, Hall, Hodge, Hu, Iliev, J. Dudley, Keisler, Knox, Knox, Komatsu, Komatsu, L. Knox, L. Shaw, Lagache, Lau, Lewis, Lueker, M. Millea, McQuinn, Navarro, O. Doré, O. Zahn, Peacock, Planck Collaboration., Prunet, Puget, Santos, Scott, Sehgal, Shaw, Shaw, Shirokoff, Tegmark, Tegmark, Tinker, Trac, Vieira, Viero, White, Wright, Y.-S. Song, Zahn, Zahn, Zhang   +54 more
core   +2 more sources

Machine learning models predict the emergence of depression in Argentinean college students during periods of COVID-19 quarantine

Frontiers in Psychiatry
IntroductionThe COVID-19 pandemic has exacerbated mental health challenges, particularly depression among college students. Detecting at-risk students early is crucial but remains challenging, particularly in developing countries.
Lorena Cecilia López Steinmetz, Lorena Cecilia López Steinmetz, Margarita Sison, Rustam Zhumagambetov, Juan Carlos Godoy, Stefan Haufe, Stefan Haufe, Stefan Haufe, Stefan Haufe   +8 more
doaj   +1 more source

Unifying Multi-Modal Uncertainty Modeling and Semantic Alignment for Text-to-Image Person Re-identification

AAAI Conference on Artificial Intelligence
Text-to-Image person re-identification (TI-ReID) aims to retrieve the images of target identity according to the given textual description. The existing methods in TI-ReID focus on aligning the visual and textual modalities through contrastive feature ...
Zhiwei Zhao, Bin Liu, Yan Lu, Qi Chu, Nenghai Yu   +4 more
semanticscholar   +1 more source

DropConnect is effective in modeling uncertainty of Bayesian deep networks [PDF]

Scientific Reports, 2019
Deep neural networks (DNNs) have achieved state-of-the-art performance in many important domains, including medical diagnosis, security, and autonomous driving.
Aryan Mobiny, H. Nguyen, S. Moulik, Naveen Garg, Carol C. Wu   +4 more
semanticscholar   +1 more source

Data granulation by the principles of uncertainty [PDF]

, 2015
Researches in granular modeling produced a variety of mathematical models, such as intervals, (higher-order) fuzzy sets, rough sets, and shadowed sets, which are all suitable to characterize the so-called information granules.
Livi, Lorenzo, Sadeghian, Alireza
core   +1 more source

Probabilistic Conflict Detection Using Heteroscedastic Gaussian Process and Bayesian Optimization

IEEE Access, 2023
Conflict detection plays a crucial role in ensuring flight safety and efficiency and is a critical component of an air traffic control system. Despite the availability of tools to support air traffic controllers in identifying potential conflicts, their ...
Duc-Thinh Pham, Yash Guleria, Sameer Alam, Vu Duong   +3 more
doaj   +1 more source