This paper presents a preliminary study about the design of an intelligent on-line monitoring system to urban environment modeling and prediction. The area of interest is that of the small town of Villa San Giovanni, in Southern Italy, which experiences a very peculiar condition of practical as well as scientific appeal. NNs are used as a basis for modeling interactions among many variables in order to predict well in advance a strong pollution episode may take place. The NN model is supported by a fuzzy knowledge based system which is able to extract the underlying correlation among different types of variables. The fuzzy logic approach is also used to derive statement which may help local politicians to explain their planned actions in order to prevent acute pollution episodes.

A Fuzzy Neural Network for Urban Environment Monitoring System: the Villa San Giovanni study case / Marino, D.; Morabito, Francesco Carlo. - (1999), pp. 323-328. (Intervento presentato al convegno Neural Nets, WIRN,Vietri-99, Proc. 11th Workshop, Springer Verlag tenutosi a Vietri Sul Mare, Salerno, Italy nel 20–22 May 1999) [10.1007/978-1-4471-0877-1_38].

A Fuzzy Neural Network for Urban Environment Monitoring System: the Villa San Giovanni study case

MARINO D.
;
MORABITO, Francesco Carlo
1999-01-01

Abstract

This paper presents a preliminary study about the design of an intelligent on-line monitoring system to urban environment modeling and prediction. The area of interest is that of the small town of Villa San Giovanni, in Southern Italy, which experiences a very peculiar condition of practical as well as scientific appeal. NNs are used as a basis for modeling interactions among many variables in order to predict well in advance a strong pollution episode may take place. The NN model is supported by a fuzzy knowledge based system which is able to extract the underlying correlation among different types of variables. The fuzzy logic approach is also used to derive statement which may help local politicians to explain their planned actions in order to prevent acute pollution episodes.
1999
1-85233-177-1
Wind Direction; Fuzzy Neural Network; Pollution Episode; Fuzzy Logic Approach; Underlying Correlation
File in questo prodotto:
File Dimensione Formato  
Marino_1999_Fuzzy_Network_editor.pdf

solo utenti autorizzati

Tipologia: Versione Editoriale (PDF)
Licenza: Copyright dell'editore
Dimensione 446.13 kB
Formato Adobe PDF
446.13 kB Adobe PDF   Visualizza/Apri   Richiedi una copia

I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.

Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.12318/14738
Citazioni
  • ???jsp.display-item.citation.pmc??? ND
  • Scopus ND
  • ???jsp.display-item.citation.isi??? 7
social impact