An Operationally Adaptive System for Rapid Acoustic Transmission Loss Prediction

An operationally adaptive (OA) system for prediction of acoustic transmission loss (TL) in the atmosphere is developed in this paper. This system uses expert neural network predictors, each corresponding to a specific range of source elevation. The outputs of the expert predictors are combined using...

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Bibliographic Details
Main Authors: McCarron, Michael, Azimi-Sadjadi, Mahmood R., Wichern, Gordon, Mungiole, Michael
Format: Conference Proceeding
Language:English
Subjects:
Acoustic propagation
Adaptive systems
Atmosphere
Atmospheric modeling
Equations
Function approximation
Interference
Neural networks
Predictive models
Propagation losses
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Summary:An operationally adaptive (OA) system for prediction of acoustic transmission loss (TL) in the atmosphere is developed in this paper. This system uses expert neural network predictors, each corresponding to a specific range of source elevation. The outputs of the expert predictors are combined using a performance-aware weighting mechanism and a nonlinear fusion system. Using this prediction methodology the computational intractability of traditional acoustic models is eliminated. The proposed system is tested on a synthetically generated acoustic data set for a wide range of geometric, source, and environmental conditions.
ISSN:2161-4393
2161-4407
DOI:10.1109/IJCNN.2007.4371310