A
Aida Calviño
Researcher at Complutense University of Madrid
Publications - 25
Citations - 457
Aida Calviño is an academic researcher from Complutense University of Madrid. The author has contributed to research in topics: Random variable & Probabilistic logic. The author has an hindex of 11, co-authored 24 publications receiving 386 citations. Previous affiliations of Aida Calviño include Carlos III Health Institute & University of Cantabria.
Papers
More filters
Journal ArticleDOI
A State-of-the-Art Review of the Sensor Location, Flow Observability, Estimation, and Prediction Problems in Traffic Networks
TL;DR: A state-of-the-art review of flow observability, estimation, and prediction problems in traffic networks is performed to consider them as different optimization problems whose data, variables, constraints, and objective functions are the main elements that characterize the problems proposed by different authors.
Journal ArticleDOI
Modeling the Probability of Sustained Virological Response to Therapy with Pegylated Interferon plus Ribavirin in Patients Coinfected with Hepatitis C Virus and HIV
Jose Medrano,Karin Neukam,Norma Rallón,Antonio Rivero,Salvador Resino,Susanna Naggie,Antonio Caruz,Aida Calviño,Juan Macías,José Miguel Benito,Carlos Sánchez-Piedra,Eugenia Vispo,Pablo Barreiro,John G. McHutchison,Juan A. Pineda,Vincent Soriano +15 more
TL;DR: The probability of achieving sustained virological response with pegIFN-RBV therapy in HIV-HCV-coinfected patients can be reliably estimated prior to initiation of therapy using an index that includes 4 noninvasive parameters.
Journal ArticleDOI
On the Probabilistic and Physical Consistency of Traffic Random Variables and Models
TL;DR: The consistency of stochastic traffic models from the points of view of probability and statistics and also from a dimensional analysis perspective are presented and some proposed models in the literature are analyzed.
Journal ArticleDOI
A Markovian-Bayesian Network for Risk Analysis of High Speed and Conventional Railway Lines Integrating Human Errors
Enrique Castillo,Aida Calviño,Zacarías Grande,Santos Sánchez-Cambronero,Inmaculada Gallego,Ana Rivas,José María Menéndez +6 more
TL;DR: A new Markovian–Bayesian network model is provided to evaluate the probability of accident associated with the circulation of trains along a given high speed or conventional railway line with special consideration to human error to generate a continuously increasing risk graph.
Journal ArticleDOI
Bayesian Networks-Based Probabilistic Safety Analysis for Railway Lines
TL;DR: A Bayesian network model is developed, in which all the items or elements encountered when travelling a railway line, such as terrain, infrastructure, light signals, speed limit signs, curves, switches, tunnels, viaducts, rolling stock, and any other element related to its safety are reproduced.