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.

COGNITIVE MODELS FOR ADAPTIVE MONITORING SYSTEM

GIORDANO R;URICCHIO VF;VURRO M
2007

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.
2007
Istituto di Ricerca Sulle Acque - IRSA
Inglese
Vincenzo Di Lecce; Enrique H. Ruspini
Proceedings of the 2007 IEEE International Conference on Computational Intelligence for Measurement Systems and Applications
COMPUTATIONAL INTELLIGENCE FOR MEASUREMENT SYSTEMS AND APPLICATIONS - CIMSA 2007, IEEE INT. CONF.
07EX1621C
110
115
6
1-4244-0824-5
http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=4362549&tag=1
IEEE, Institute of electrical and electronics engineers
New York
STATI UNITI D'AMERICA
Sì, ma tipo non specificato
27-29 June 2007
OSTUNI (BR)
Fuzzy Cognitive Map
Monitoring Information System
Problem Structuring Methods
3
none
GIORDANO R.; URICCHIO V.F.; VURRO M.
273
info:eu-repo/semantics/conferenceObject
04 Contributo in convegno::04.01 Contributo in Atti di convegno
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/20.500.14243/115137
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