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DatoValore
TitleCOGNITIVE MODELS FOR ADAPTIVE MONITORING SYSTEM
AbstractThe 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.
SourceCOMPUTATIONAL INTELLIGENCE FOR MEASUREMENT SYSTEMS AND APPLICATIONS - CIMSA 2007, IEEE INT. CONF., OSTUNI (BR), 27-29 June 2007
KeywordsFuzzy Cognitive MapMonitoring Information SystemProblem Structuring Methods
Year2007
TypeContributo in atti di convegno
DOI10.1109/CIMSA.2007.4362549
AuthorsGIORDANO R.; URICCHIO V.F.; VURRO M.
Text89496 2007 10.1109/CIMSA.2007.4362549 ISI Web of Science WOS 000251008000022 Fuzzy Cognitive Map Monitoring Information System Problem Structuring Methods COGNITIVE MODELS FOR ADAPTIVE MONITORING SYSTEM GIORDANO R.; URICCHIO V.F.; VURRO M. Water Research Institute I.R.S.A., Italian National Research Council C.N.R., Viale F. de Blasio, 5 700123 Bari, Italy 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. Proceedings of the 2007 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Vincenzo Di Lecce; Enrique H. Ruspini 1 4244 0824 5 http //ieeexplore.ieee.org/xpls/abs_all.jsp arnumber=4362549 tag=1 07EX1621C COMPUTATIONAL INTELLIGENCE FOR MEASUREMENT SYSTEMS AND APPLICATIONS CIMSA 2007, IEEE INT. CONF. OSTUNI BR 27 29 June 2007 Internazionale Contributo Cognitive Models for Adaptive Monitoring System 04362549.pdf Contributo in atti di convegno Institute of Electrical and Electronics Engineers 2159 1547 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Print IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Print IEEE Int. Conf. Comput. Intell. Meas. Syst. Appl. Print IEEE International Conference on Computational Intelligence for Measurement Systems and Applications Print International Conference on Computational Intelligence for Measurement Systems and Applications Print Computational intelligence for measurement systems and applications Print CIMSA proceedings Print vitofelice.uricchio URICCHIO VITO FELICE raffaele.giordano GIORDANO RAFFAELE michele.vurro VURRO MICHELE TA.P04.005.007 Strumenti di mitigazione dello stress quali quantitativo per i sistemi idrici