Results 31 to 40 of about 207,453 (329)
Integration of Bayesian Networks with GIS for Dynamic Avalanche Hazard Assessment: NSDI Perspective
Doğal Afetler ve Çevre Dergisi, 2018 Natural hazard assessments are core to risk definition and early warning systems and play a fundamental role in the prevention of major damages. Traditional hazard identification methods are static.
Ipek Yilmaz, Derya Ozturk
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Cerebral modeling and dynamic Bayesian networks [PDF]
Artificial Intelligence in Medicine, 2004 The understanding and the prediction of the clinical outcomes of focal or degenerative cerebral lesions, as well as the assessment of rehabilitation procedures, necessitate knowing the cerebral substratum of cognitive or sensorimotor functions. This is achieved by activation studies, where subjects are asked to perform a specific task while data of ...
Labatut, Vincent +4 more
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Exploiting sparsity and sharing in probabilistic sensor data models [PDF]
, 2008 Probabilistic sensor models defined as dynamic Bayesian networks can possess an inherent sparsity that is not reflected in the structure of the network. Classical inference algorithms like variable elimination and junction tree propagation cannot exploit
Evers, S.
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Articulatory feature recognition using dynamic Bayesian networks [PDF]
Computer Speech & Language, 2004 We describe a dynamic Bayesian network for articulatory feature recognition. The model is intended to be a component of a speech recognizer that avoids the problems of conventional ''beads-on-a-string'' phoneme-based models. We demonstrate that the model gives superior recognition of articulatory features from the speech signal compared with a state-of-
Frankel, Joe +2 more
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Dynamic Bayesian networks in molecular plant science: inferring gene regulatory networks from multiple gene expression time series [PDF]
, 2011 To understand the processes of growth and biomass production in plants, we ultimately need to elucidate the structure of the underlying regulatory networks at the molecular level.
Dondelinger, F., Husmeier, D., Lebre, S.
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Algorithms, 2020 Dynamic Bayesian networks (DBNs) represent complex time-dependent causal relationships through the use of conditional probabilities and directed acyclic graph models.
Austin D. Lewis, Katrina M. Groth
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Quantifying resilience of socio-ecological systems through dynamic Bayesian networks
Frontiers in Forests and Global Change, 2022 Quantifying resilience of socio-ecological systems (SES) can be invaluable to delineate management strategies of natural resources and aid the resolution of socio-environmental conflicts.
Felipe Franco-Gaviria +4 more
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Examining the dynamics of macroeconomic indicators and banking stock returns with bayesian networks [PDF]
, 2019 According to the modern portfolio theory, the direction of the relationship between the securities in the portfolio is stated to be effective in reducing the risk. Moreover, securities in high correlation are avoided by taking place in the same portfolio.
Fatma Busem, Hatipoğlu, Uyar, Umut
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IEEE Access, 2018 A novel reliability evaluation methodology of complex systems is proposed using dynamic object-oriented Bayesian networks (DOOBNs). This modeling methodology consists of two main phases, namely, construction phases for object-oriented Bayesian networks ...
Xiaobing Yuan +6 more
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A Random Traffic Assignment Model for Networks Based on Discrete Dynamic Bayesian Algorithms
Discrete Dynamics in Nature and Society, 2022 In this paper, a stochastic traffic assignment model for networks is proposed for the study of discrete dynamic Bayesian algorithms. In this paper, we study a feasible method and theoretical system for implementing traffic engineering in networks based ...
Wei Zhou
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