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New Risk Management Findings from Texas A&M University Described (Power Outage Estimation for Tropical Cyclones: Improved Accuracy with Simpler...

August 1, 2014



New Risk Management Findings from Texas A&M University Described (Power Outage Estimation for Tropical Cyclones: Improved Accuracy with Simpler Models)

By a News Reporter-Staff News Editor at Insurance Weekly News -- Researchers detail new data in Risk Management. According to news reporting originating from College Station, Texas, by VerticalNews correspondents, research stated, "In this article, we discuss an outage-forecasting model that we have developed. This model uses very few input variables to estimate hurricane-induced outages prior to landfall with great predictive accuracy."

Our news editors obtained a quote from the research from Texas A&M University, "We also show the results for a series of simpler models that use only publicly available data and can still estimate outages with reasonable accuracy. The intended users of these models are emergency response planners within power utilities and related government agencies. We developed our models based on the method of random forest, using data from a power distribution system serving two states in the Gulf Coast region of the United States. We also show that estimates of system reliability based on wind speed alone are not sufficient for adequately capturing the reliability of system components."

According to the news editors, the research concluded: "We demonstrate that a multivariate approach can produce more accurate power outage predictions."

For more information on this research see: Power Outage Estimation for Tropical Cyclones: Improved Accuracy with Simpler Models. Risk Analysis, 2014;34(6):1069-1078. Risk Analysis can be contacted at: Wiley-Blackwell, 111 River St, Hoboken 07030-5774, NJ, USA. (Wiley-Blackwell - www.wiley.com/; Risk Analysis - onlinelibrary.wiley.com/journal/10.1111/(ISSN)1539-6924)

The news editors report that additional information may be obtained by contacting R. Nateghi, Texas A&M University, Dept. of Geog, College Stn, TX, United States. Additional authors for this research include S. Guikema and S.M. Quiring.

Keywords for this news article include: College Station, Texas, United States, North and Central America, Risk Management

Our reports deliver fact-based news of research and discoveries from around the world. Copyright 2014, NewsRx LLC


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Source: Insurance Weekly News


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