http://www.cnr.it/ontology/cnr/individuo/prodotto/ID89496
COGNITIVE MODELS FOR ADAPTIVE MONITORING SYSTEM (Contributo in atti di convegno)
- Type
- Label
- COGNITIVE MODELS FOR ADAPTIVE MONITORING SYSTEM (Contributo in atti di convegno) (literal)
- Anno
- 2007-01-01T00:00:00+01:00 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#doi
- 10.1109/CIMSA.2007.4362549 (literal)
- Alternative label
GIORDANO R.; URICCHIO V.F.; VURRO M. (2007)
COGNITIVE MODELS FOR ADAPTIVE MONITORING SYSTEM
in COMPUTATIONAL INTELLIGENCE FOR MEASUREMENT SYSTEMS AND APPLICATIONS - CIMSA 2007, IEEE INT. CONF., OSTUNI (BR), 27-29 June 2007
(literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#autori
- GIORDANO R.; URICCHIO V.F.; VURRO M. (literal)
- Pagina inizio
- Pagina fine
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#url
- http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4362549&tag=1 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#titoloVolume
- Proceedings of the 2007 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#numeroVolume
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#note
- ATTI SU CD-ROM
27/06/2007 - 29/06/2007 (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#pagineTotali
- Note
- ISI Web of Science (WOS) (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#affiliazioni
- Water Research Institute--I.R.S.A., Italian National Research Council--C.N.R., Viale F. de Blasio, 5-700123 Bari, Italy (literal)
- Titolo
- COGNITIVE MODELS FOR ADAPTIVE MONITORING SYSTEM (literal)
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#isbn
- Http://www.cnr.it/ontology/cnr/pubblicazioni.owl#curatoriVolume
- Vincenzo Di Lecce; Enrique H. Ruspini (literal)
- Abstract
- The transition towards new approaches to water resources management to deal with complexity demands changes in the role of information in decision-making. These approaches proceed from the premise that policies can be treated as experiments in which monitoring outcomes are evaluated to judge what has been learned. Thus monitoring becomes increasingly important for learning about the system and assessing management strategies along with modelling and other knowledge exploring techniques. To play this important role in water management, novel and integrated monitoring systems are required to support both the learning and decision making processes. In this paper a methodology to support the design of monitoring system for water management in the age of complexity has been described. The methodology is based on the integration between problem structuring methods and fuzzy logic to collect and structure the knowledge of experts and stakeholders. (literal)
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