Andere Kunden interessierten sich auch für
![Predicting Launch Pad Winds at the Kennedy Space Center with a Neural Network Model]( "Predicting Launch Pad Winds at the Kennedy Space Center with a Neural Network Model")
Predicting Launch Pad Winds at the Kennedy Space Center with a Neural Network Model60,99 €![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 Station63,99 €![Efficient Low-Speed Flight in a Wind Field]( "Efficient Low-Speed Flight in a Wind Field")
Efficient Low-Speed Flight in a Wind Field61,99 €![Improving Cape Canaveral's Next-Day Thunderstorm Forecasting Using a Meso-Eta Model-Based Index]( "Improving Cape Canaveral's Next-Day Thunderstorm Forecasting Using a Meso-Eta Model-Based Index")
Improving Cape Canaveral's Next-Day Thunderstorm Forecasting Using a Meso-Eta Model-Based Index60,99 €![Descriptive and Conditional Climatology for Cpecific Launch Commit Criteria for Cape Canaveral, Florida]( "Descriptive and Conditional Climatology for Cpecific Launch Commit Criteria for Cape Canaveral, Florida")
Descriptive and Conditional Climatology for Cpecific Launch Commit Criteria for Cape Canaveral, Florida64,99 €![Evolutionary Artificial Neural Network Weight Tuning to Optimize Decision Making for an Abstract Game]( "Evolutionary Artificial Neural Network Weight Tuning to Optimize Decision Making for an Abstract Game")
Evolutionary Artificial Neural Network Weight Tuning to Optimize Decision Making for an Abstract Game60,99 €![A Radial Basis Function Neural Network Approach to Two-Color Infrared Missile Detection]( "A Radial Basis Function Neural Network Approach to Two-Color Infrared Missile Detection")
A Radial Basis Function Neural Network Approach to Two-Color Infrared Missile Detection63,99 €
This thesis demonstrates the potential for using time-delay neural networks to provide Launch Weather Officers (LWOs) at 45th Weather Squadron (45 WS) with advance warning of wintertime (November-March) peak wind speeds at the Atlas launch pad. The 45 WS provides weather support to the United States space program at Cape Canaveral Air Station, NASA's Kennedy Space Center, and Patrick Air Force Base. Due to the complex wintertime environment produced by the effects of friction and instability, 45 WS LWOs consider wintertime launch pad winds their toughest forecast challenge. Neural networks were developed, trained, and tested using observations of wintertime peak wind speed, wind direction, and directional deviation collected from March 1995 through March 1999 by 45th Space Wing's Weather Information Network Display System. Using current and past values of the observed elements, the networks produced 16 forecasts of peak wind speed. The first forecast was valid for 30 minutes past forecast start time, the second for 1 hour past start time, etc., up to 8 hours past start time, for any start time. Network performance was compared to three other forecasting options: persistence, climatology, and randomly selecting wind speeds from a climatologically based distribution. For forecasts at the end of the forecast period, networks that were tested with data near in time to the networks` training data showed skill over the other forecasting options.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.
Hinweis: Dieser Artikel kann nur an eine deutsche Lieferadresse ausgeliefert werden.