Determining Public Structure Crowd Evacuation Capacity
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[1] Yuan Cheng,et al. Modeling cooperative and competitive behaviors in emergency evacuation: A game-theoretical approach , 2011, Comput. Math. Appl..
[2] Dinesh Manocha,et al. Directing Crowd Simulations Using Navigation Fields , 2011, IEEE Transactions on Visualization and Computer Graphics.
[3] G. Octo Barnett,et al. DXplain on the Internet , 1998, AMIA.
[4] Nir Friedman,et al. The Bayesian Structural EM Algorithm , 1998, UAI.
[5] Bev Littlewood,et al. Applying Bayesian Belief Networks to System Dependability Assessment , 1996, SSS.
[6] Seungho Lee,et al. Crowd Simulation for Emergency Response using BDI Agent Based on Virtual Reality , 2006, Proceedings of the 2006 Winter Simulation Conference.
[7] Judea Pearl,et al. Fusion, Propagation, and Structuring in Belief Networks , 1986, Artif. Intell..
[8] R. Colombo,et al. A Macroscopic model for Pedestrian Flows in Panic Situations , 2010 .
[9] Tony White,et al. Microscopic information processing and communication in crowd dynamics , 2010 .
[10] Pedro Larrañaga,et al. Learning Bayesian network structures by searching for the best ordering with genetic algorithms , 1996, IEEE Trans. Syst. Man Cybern. Part A.
[11] Ameya Shendarkar,et al. Crowd simulation for emergency response using BDI agents based on immersive virtual reality , 2008, Simul. Model. Pract. Theory.
[12] Gregory F. Cooper,et al. A Bayesian method for the induction of probabilistic networks from data , 1992, Machine Learning.
[13] Stuart J. Russell,et al. A Logical Approach to Reasoning by Analogy , 1987, IJCAI.
[14] Krzysztof Kulakowski,et al. Crowd dynamics - being stuck , 2011, Comput. Phys. Commun..
[15] Dominic A. Clark,et al. Representing uncertain knowledge - an artificial intelligence approach , 1993 .
[16] A. Seyfried,et al. Methods for measuring pedestrian density, flow, speed and direction with minimal scatter , 2009, 0911.2165.
[17] Majid Sarvi,et al. Animal dynamics based approach for modeling pedestrian crowd egress under panic conditions , 2011 .
[18] S. Wong,et al. A higher-order macroscopic model for pedestrian flows , 2010 .
[19] Solomon Eyal Shimony,et al. Bayes Networks for Sonar Sensor Fusion , 1997, UAI.
[20] Andreas Krause,et al. Unfreezing the robot: Navigation in dense, interacting crowds , 2010, 2010 IEEE/RSJ International Conference on Intelligent Robots and Systems.
[21] Richard O. Duda,et al. Subjective bayesian methods for rule-based inference systems , 1976, AFIPS '76.
[22] Lakhmi C. Jain,et al. Introduction to Bayesian Networks , 2008 .
[23] I. Good. A CAUSAL CALCULUS (I)* , 1961, The British Journal for the Philosophy of Science.
[24] David J. Spiegelhalter,et al. Local computations with probabilities on graphical structures and their application to expert systems , 1990 .
[25] W. F. Rousseau,et al. A method for computing probabilities in complex situations , 1968 .
[26] Christian Dogbe. On the Cauchy problem for macroscopic model of pedestrian flows , 2010 .
[27] Thomas G. Dietterich. What is machine learning? , 2020, Archives of Disease in Childhood.
[28] Ronald A. Howard,et al. Influence Diagrams , 2005, Decis. Anal..
[29] Erica D. Kuligowski,et al. Pedestrian and Evacuation Dynamics , 2011 .
[30] Keinosuke Fukunaga,et al. A Branch and Bound Algorithm for Feature Subset Selection , 1977, IEEE Transactions on Computers.
[31] Brendan J. Frey,et al. Graphical Models for Machine Learning and Digital Communication , 1998 .
[32] Judea Pearl,et al. Probabilistic reasoning in intelligent systems - networks of plausible inference , 1991, Morgan Kaufmann series in representation and reasoning.
[33] Thiago Tinoco Pires,et al. An approach for modeling human cognitive behavior in evacuation models , 2005 .
[34] Kazuo J. Ezawa,et al. Fraud/Uncollectible Debt Detection Using a Bayesian Network Based Learning System: A Rare Binary Outcome with Mixed Data Structures , 1995, UAI.
[35] Harri Ehtamo,et al. Counterflow model for agent-based simulation of crowd dynamics , 2012 .
[36] N. Wermuth,et al. Graphical Models for Associations between Variables, some of which are Qualitative and some Quantitative , 1989 .
[37] Gregory F. Cooper,et al. NESTOR: A Computer-Based Medical Diagnostic Aid That Integrates Causal and Probabilistic Knowledge. , 1984 .
[38] Nicola Bellomo,et al. On the Modeling of Traffic and Crowds: A Survey of Models, Speculations, and Perspectives , 2011, SIAM Rev..