Neural-Network-Based Fuzzy Logic Control and Decision System
IEEE Transactions on Computers - Special issue on artificial neural networks
Fuzzy sets and fuzzy logic: theory and applications
Fuzzy sets and fuzzy logic: theory and applications
Neural Networks: A Comprehensive Foundation (3rd Edition)
Neural Networks: A Comprehensive Foundation (3rd Edition)
Parallel consensual neural networks
IEEE Transactions on Neural Networks
Training feedforward networks with the Marquardt algorithm
IEEE Transactions on Neural Networks
Rapid acoustic transmission loss prediction using an operationally adaptive system
IJCNN'09 Proceedings of the 2009 international joint conference on Neural Networks
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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 of the system showed root mean square (RMS) errors of 1.84 dB for the nonturbulent and 1.36 dB for the turbulent conditions, respectively, which are acceptable levels for near real-time performance. Additionally, the environmentally adaptive system demonstrated improved TL prediction accuracy at high frequencies and large values of horizontal separation between source and receiver.