Computational Intelligence for Disaster Planning and Mitigation
Wed, Jan 26, 2022 10:00 AM - 11:00 AM EST
Abstract: Infrastructure planning and restoration following a disaster is a complex problem requiring the integration of multiple data types and the evaluation of complex and potentially nonlinear relationships. This research uses publicly available data sets shared by the United States Geological Survey (The National Map, Digital Elevation Models, seismic data), the United States Army Corps of Engineers (River Discharge data, Lock & Dam and Levee inventory), and the U.S. National Weather Service (rainfall data, predicted weather patterns). This body of work examines evolutionary computation for infrastructure restoration planning in the aftermath of tornadoes and earthquakes. The use of neural networks is considered to predict changing water levels to capture the timing and impact of flooding and flash flooding events on transportation infrastructure. Algorithms have been used to develop plans for rerouting traffic to minimize the impact of the flooding event on the transportation system, as well as the risk to human lives. This allows emergency management and transportation engineering managers to make better decisions related to safety and the restoration of critical infrastructure elements.
Webinar Speaker: Prof. Steven M. Corns
Webinar Chair: Dr. Sansanee Auephanwiriyakul
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