An Environmentally Adaptive System for Rapid Acoustic Transmission Loss Prediction

An environmentally adaptive 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 environmental condition. The outputs of the expert predictors are combined using a fuzzy confidence measure and a non-linear fusion system. Using this prediction methodology the computational intractability of traditional acoustic models is eliminated. The proposed system is tested on a synthetic acoustic data set for a wide range of geometric, source, and environmental conditions.

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