http://www.cnr.it/ontology/cnr/individuo/prodotto/ID8099
Wavelets and Elman neural networks for monitoring environmental variables (Articolo in rivista)
- Type
- Label
- Wavelets and Elman neural networks for monitoring environmental variables (Articolo in rivista) (literal)
- Anno
- 2007-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1016/j.cam.2007.10.040 (literal)
- Alternative label
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- Ciarlini P., Maniscalco U. (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Rivista
- Note
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Istituto per le Applicazioni del Calcolo \"Mauro Picone\", Viale del Policlinico 137, 00161 Roma, Italy (literal)
- Titolo
- Wavelets and Elman neural networks for monitoring environmental variables (literal)
- Abstract
- 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. (literal)
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