Bayesian learning of models for estimating uncertainty in alert systems: Application to air traffic conflict avoidance
نویسندگان
چکیده
منابع مشابه
MINLP in Air Traffic Management: Aircraft conflict avoidance
Air Traffic Management (ATM) represents a domain of emerging and challenging applications of MINLP. A number of problems arising in ATM lead naturally to optimization problems whose efficient and reliable solution constitutes a key ingredient to ensure air traffic safety [11]. The air-traffic level currently attained in Europe is around tens of thousands of flights per day, and it is expected t...
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15 صفحه اولAir traffic flow management under uncertainty: application of chance constraints
This paper is part of the ONBOARD1 project, whose goal is to investigate the incorporation of probabilistic information about the levels of uncertainty in ATFM. The efficiency of ATFM optimizations in preventing local demand-capacity imbalances is reliant on accurate predictions of future capacity states. However these predictions are inherently uncertain due to factors such as weather effects ...
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Bayesian Model Averaging (BMA), computationally feasible using Markov Chain Monte Carlo (MCMC), is a well-known method for reliable estimation of predictive distributions. The use of decision tree (DT) models for the averaging enables experts not only to estimate a predictive posterior but also to interpret models of interest and estimate the importance of predictor factors that are assumed to ...
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ژورنال
عنوان ژورنال: Integrated Computer-Aided Engineering
سال: 2018
ISSN: 1069-2509,1875-8835
DOI: 10.3233/ica-180567