Wavelets and Elman Neural Networks for monitoring environmental variables

[摘要] An application in cultural heritage is introduced. Wavelet decomposition and Neural Networks like virtual sensors are jointly used to simulate physical and chemical measurements in specific locations of a monument, Virtual sensors, suitably trained and tested, can substitute real sensors in monitoring the monument surface quality, while the real ones should be installed for a long time and at high costs. The application of the wavelet decomposition to the environmental data series allows getting the treatment of underlying temporal structure at low frequencies. Consequently a separate training Of Suitable Elman Neural Networks for high/low components can be performed, thus improving the networks convergence in learning time and measurement accuracy in working time. (C) 2008 Published by Elsevier B.V.

[发布日期] 2008-11-15

[效力级别]  Proceedings Paper

[关键词] Wavelet pre-processing;Recursive Neural Network