Systems and methods for real-time data processing and for emergency planning
Abstract
Systems and methods are described herein for real-time data processing and for emergency planning. Scenario test data may be collected in real-time based on monitoring local or regional data to ascertain any anomaly phenomenon that may indicate an imminent danger or of concern. A computer-implemented method may include filtering a plurality of different test scenarios to identify a sub-set of test scenarios from the plurality of different test scenarios that may have similar behavior characteristics. A sub-set of test scenarios is provided to a trained neural network to identify one or more sub-set of test scenarios. The one or more identified sub-set of test scenarios may correspond to one or more anomaly test scenarios from the sub-set of test scenarios that is most likely to lead to an undesirable outcome. The neural network may be one of: a conventional neural network and a modular neural network.
- Inventors:
- Issue Date:
- Research Org.:
- The Ohio State Univ., Columbus, OH (United States)
- Sponsoring Org.:
- USDOE
- OSTI Identifier:
- 2222082
- Patent Number(s):
- 11720091
- Application Number:
- 17/371,940
- Assignee:
- Ohio State Innovation Foundation (Columbus, OH)
- DOE Contract Number:
- NE0008710
- Resource Type:
- Patent
- Resource Relation:
- Patent File Date: 07/09/2021
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 97 MATHEMATICS AND COMPUTING
Citation Formats
Yilmaz, Alper, Ajam Gard, Nima, Lee, Ji Hyun, Aldemir, Tunc, and Denning, Richard. Systems and methods for real-time data processing and for emergency planning. United States: N. p., 2023.
Web.
Yilmaz, Alper, Ajam Gard, Nima, Lee, Ji Hyun, Aldemir, Tunc, & Denning, Richard. Systems and methods for real-time data processing and for emergency planning. United States.
Yilmaz, Alper, Ajam Gard, Nima, Lee, Ji Hyun, Aldemir, Tunc, and Denning, Richard. Tue .
"Systems and methods for real-time data processing and for emergency planning". United States. https://www.osti.gov/servlets/purl/2222082.
@article{osti_2222082,
title = {Systems and methods for real-time data processing and for emergency planning},
author = {Yilmaz, Alper and Ajam Gard, Nima and Lee, Ji Hyun and Aldemir, Tunc and Denning, Richard},
abstractNote = {Systems and methods are described herein for real-time data processing and for emergency planning. Scenario test data may be collected in real-time based on monitoring local or regional data to ascertain any anomaly phenomenon that may indicate an imminent danger or of concern. A computer-implemented method may include filtering a plurality of different test scenarios to identify a sub-set of test scenarios from the plurality of different test scenarios that may have similar behavior characteristics. A sub-set of test scenarios is provided to a trained neural network to identify one or more sub-set of test scenarios. The one or more identified sub-set of test scenarios may correspond to one or more anomaly test scenarios from the sub-set of test scenarios that is most likely to lead to an undesirable outcome. The neural network may be one of: a conventional neural network and a modular neural network.},
doi = {},
journal = {},
number = ,
volume = ,
place = {United States},
year = {Tue Aug 08 00:00:00 EDT 2023},
month = {Tue Aug 08 00:00:00 EDT 2023}
}
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