Detection of epidemic outbreaks with Persistent Causal-Chain Dynamic Bayesian Networks
A method for determining a probability of a hidden variable from an observed variable in a Dynamic Bayesian Network is presented. The method includes identifying the network based on predetermined criteria, determining a number of hidden variables in a time slice of the network, determining a number...
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| creator | DASH DENVER |
| description | A method for determining a probability of a hidden variable from an observed variable in a Dynamic Bayesian Network is presented. The method includes identifying the network based on predetermined criteria, determining a number of hidden variables in a time slice of the network, determining a number of the time slices of the network, and determining the probability of the hidden variable from the observed variable in less than exponential time with respect to the number of hidden variables. |
| format | Patent |
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| subjects | ALARM SYSTEMS CALCULATING COMPUTER SYSTEMS BASED ON SPECIFIC COMPUTATIONAL MODELS COMPUTING COUNTING ELECTRIC DIGITAL DATA PROCESSING INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTEDFOR SPECIFIC APPLICATION FIELDS ORDER TELEGRAPHS PHYSICS SIGNALLING SIGNALLING OR CALLING SYSTEMS |
| title | Detection of epidemic outbreaks with Persistent Causal-Chain Dynamic Bayesian Networks |
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