Municipal Water Demand Forecasting: Tools for Intervention Time Series

DOI10.1080/07362994.2011.610161zbMath1232.62158OpenAlexW2082157014MaRDI QIDQ3114567

Rafael Pérez-García, J. Carlos García-Díaz, Manuel Herrera, Joaquín Izquierdo

Publication date: 19 February 2012

Published in: Stochastic Analysis and Applications (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10251/59700

zbMATH Keywords

neural networkshybrid modelsARIMA modelsintervention analysis

Mathematics Subject Classification ID

Applications of statistics to environmental and related topics (62P12) Environmental economics (natural resource models, harvesting, pollution, etc.) (91B76) Neural nets and related approaches to inference from stochastic processes (62M45)

Related Items (1)

Hybrid regression model for near real-time urban water demand forecasting

Cites Work

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• Neural network forecasting for seasonal and trend time series
• The log of the determinant of the autocorrelation matrix for testing goodness of fit in time series
• A Course in Time Series Analysis
• On a measure of lack of fit in time series models
• A proposal for a residual autocorrelation test in linear models
• A Powerful Portmanteau Test of Lack of Fit for Time Series

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