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[49210] Artykuł: Soft Computing Approaches for Urban Water Demand ForecastingCzasopismo: Intelligent Decision Technologies Tom: 57, Strony: 357-367ISSN: 2190-3018 ISBN: 978-3-319-39627-9 Wydawca: SPRINGER INT PUBLISHING AG, GEWERBESTRASSE 11, CHAM, CH-6330, SWITZERLAND Opublikowano: 2016 Seria wydawnicza: Smart Innovation Systems and Technologies Liczba arkuszy wydawniczych: 0.60 Autorzy / Redaktorzy / Twórcy Grupa MNiSW: Materiały z konferencji międzynarodowej (zarejestrowane w Web of Science) Punkty MNiSW: 15 Klasyfikacja Web of Science: Proceedings Paper ![]() ![]() ![]() Keywords: Fuzzy Cognitive Maps  Neuro-Fuzzy  Water management  Forecasting  Prediction  Decision support  |
This paper presents an integrated framework for water resources management at urban level which consists of a Neuro-Fuzzy and Fuzzy Cognitive Map-based, (FCM) decision support system (DSS) based on multiple objectives and multiple disciplines for planning and forecasting. The proposed DSS has as primary goals to: (a) adaptively control the water pressure of the water distribution system by forecasting the water demand at the urban level and (b) to reduce leakage of the water network by controlling the water pressure. The system follows a model-driven architecture with the inclusion of the FCM-based models and a spatio-temporal model for arranging all data. The validation of the proposed learning algorithms is made for two case studies that comprise different water supply characteristics and correspond to different locations in Europe.