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An Artificial Immune System-Inspired Multiobjective Evolutionary Algorithm with Application to the Detection of Distributed Computer Network Intrusion60,99 €![A Comparison of Genetic Algorithm Parametrization on Synthetic Optimization Problems]( "A Comparison of Genetic Algorithm Parametrization on Synthetic Optimization Problems")
A Comparison of Genetic Algorithm Parametrization on Synthetic Optimization Problems60,99 €![A Validation Assessment of the Storm Air-To-Air Prototype Algorithm]( "A Validation Assessment of the Storm Air-To-Air Prototype Algorithm")
A Validation Assessment of the Storm Air-To-Air Prototype Algorithm60,99 €![Use of Climatology to Predict Maximum Wintertime Wind Speeds at the Kennedy Space Center and Cape Canaveral Air Station]( "Use of Climatology to Predict Maximum Wintertime Wind Speeds at the Kennedy Space Center and Cape Canaveral Air Station")
Use of Climatology to Predict Maximum Wintertime Wind Speeds at the Kennedy Space Center and Cape Canaveral Air Station60,99 €![Designing an Algorithm to Predict the Intensity of the Severe Weather Season]( "Designing an Algorithm to Predict the Intensity of the Severe Weather Season")
Designing an Algorithm to Predict the Intensity of the Severe Weather Season60,99 €![Evaluation of Barnes' Method and Kriging for Estimating the Low Level Wind Field]( "Evaluation of Barnes' Method and Kriging for Estimating the Low Level Wind Field")
Evaluation of Barnes' Method and Kriging for Estimating the Low Level Wind Field60,99 €![Logistical Estimate of the Situation]( "Logistical Estimate of the Situation")
Logistical Estimate of the Situation60,99 €
The Air Force Weather Agency (AFWA) runs the Penn State/NCAR Mesoscale Model 5 (MM5) as their main mesoscale weather forecast model. One of the post-processing procedures is a diagnostic algorithm, which is used to help identify convective and non-convective wind gusts. Anecdotal evidence by operational forecasters who use this product identify the AFWA algorithm as habitually over-forecasting wind gusts. O. Brassuer has identified a new Wind Gust Estimate (WGE), a physically based method of computing non-convective wind gusts. The WGE surmises that Turbulent Kinetic Energy (TKE) transfers the momentum of faster upper-air winds to the surface, overcoming the buoyant energy of the surface layer. This work focuses on the conversion of Brassuer's WGE to FORTRAN code and the use of post-processed CONUS AFWA MM5 model output to estimate wind gusts by the WGE method. The WGE and AFWA methods are then categorically compared for accuracy and skill in forecasting wind gusts, to determine if the WGE method is superior to the current method. Three geographical regions are identified to determine gust sensitivities of the WGE and AFWA algorithms.