Environmentally adaptive acoustic transmission loss prediction in turbulent and nonturbulent atmospheres

An environmentally adaptive system for prediction of acoustic transmission loss (TL) in the atmosphere is developed in this paper. This system uses several back propagation 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 nonlinear fusion system. Using this prediction methodology the computational intractability of traditional acoustic model-based approaches is eliminated. The proposed TL prediction system is tested on two synthetic acoustic data sets for a wide range of geometrical, source and environmental conditions including both nonturbulent and turbulent atmospheres. Test results

• Type: Journal
• Year: 2007
• Where: NN
• Authors: Gordon Wichern, Mahmood R. Azimi-Sadjadi, Michael Mungiole
• Keywords: Acoustic Transmission Loss, Environmental Conditions, Neural Network Predictors, Neural Networks, NN 2007