In this paper two new approaches, the neural network and fuzzy logic, for noise pollution evaluation, are compared. Both the proposed approaches have shown good approximation performances as confirmed by the values of same indexes, that have been computed. In particular the fuzzy approach seems to work slightly better than the neural networks, due to their interpolation capability, considered; on the other side, the fuzzy approach should work better when real data must be interpolated by using some model.

Comparison of Innovative Approaches to Noise Pollution Evaluation

FICHERA, Alberto;GRAZIANI, Salvatore;MARLETTA, Luigi
1994

Abstract

In this paper two new approaches, the neural network and fuzzy logic, for noise pollution evaluation, are compared. Both the proposed approaches have shown good approximation performances as confirmed by the values of same indexes, that have been computed. In particular the fuzzy approach seems to work slightly better than the neural networks, due to their interpolation capability, considered; on the other side, the fuzzy approach should work better when real data must be interpolated by using some model.
0931784271
acoustic noise; fuzzy logic; noise pollutioncontrol
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11769/88165
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