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|Title:||Wind Shear Forecasting by Chaotic Oscillatory-based Neural Networks (CONN) with Lee Oscillator (Retrograde Signalling) Model|
|Authors:||Wong, Max H. Y.|
Lee, Raymond S. T.
Liu, James N. K.
|Source:||IJCNN 2008 : proceedings of the International Joint Conference on Neural Networks : Hong Kong, China, June 1-6, 2008, p. 2040-2047.|
|Abstract:||Wind shear is a conventionally unpredictable meteorological phenomenon which presents a common danger to aircraft, particularly on takeoff and landing at airports. This paper describes a method for forecasting wind shear using an advanced paradigm from computational intelligence, chaotic oscillatory-based neural networks (CONN). The method uses weather data to predict wind velocities and directions over a short time period. This approach may have a wide variety of applications but from the aviation forecast perspective, it can be used in aviation to generate wind shear alerts.|
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|Appears in Collections:||COMP Conference Papers & Presentations|
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