A Short-Term Water Demand Forecasting Model Using a Moving Window on Previously Observed Data
Published 2017 View Full Article
- Home
- Publications
- Publication Search
- Publication Details
Title
A Short-Term Water Demand Forecasting Model Using a Moving Window on Previously Observed Data
Authors
Keywords
-
Journal
Water
Volume 9, Issue 3, Pages 172
Publisher
MDPI AG
Online
2017-02-28
DOI
10.3390/w9030172
References
Ask authors/readers for more resources
Related references
Note: Only part of the references are listed.- Detection of Water Meter Under-Registration Using Statistical Algorithms
- (2016) Iñigo Monedero et al. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
- Detection of Water Meter Under-Registration Using Statistical Algorithms
- (2016) Iñigo Monedero et al. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
- Pump as turbine implementation in a dynamic numerical model: cost analysis for energy recovery in water distribution network
- (2015) Mauro De Marchis et al. JOURNAL OF HYDROINFORMATICS
- Medium-Term Urban Water Demand Forecasting with Limited Data Using an Ensemble Wavelet–Bootstrap Machine-Learning Approach
- (2015) Mukesh K. Tiwari et al. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
- Assessment of predictive uncertainty within the framework of water demand forecasting using the Model Conditional Processor (MCP)
- (2015) S. Alvisi et al. Urban Water Journal
- Urban Residential Water Demand Prediction Based on Artificial Neural Networks and Time Series Models
- (2015) Muhammad A. Al-Zahrani et al. WATER RESOURCES MANAGEMENT
- Medium-Term Urban Water Demand Forecasting with Limited Data Using an Ensemble Wavelet–Bootstrap Machine-Learning Approach
- (2015) Mukesh K. Tiwari et al. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
- Adaptive water demand forecasting for near real-time management of smart water distribution systems
- (2014) Michele Romano et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Pumps as turbines (PATs) in water distribution networks affected by intermittent service
- (2014) Valeria Puleo et al. JOURNAL OF HYDROINFORMATICS
- Water Demand Forecasting Model for the Metropolitan Area of São Paulo, Brazil
- (2014) Cláudia Cristina dos Santos et al. WATER RESOURCES MANAGEMENT
- A fully adaptive forecasting model for short-term drinking water demand
- (2013) M. Bakker et al. ENVIRONMENTAL MODELLING & SOFTWARE
- Urban Water Demand Forecasting: Review of Methods and Models
- (2012) Emmanuel A. Donkor et al. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
- Comparison of multiple linear and nonlinear regression, autoregressive integrated moving average, artificial neural network, and wavelet artificial neural network methods for urban water demand forecasting in Montreal, Canada
- (2011) Jan Adamowski et al. WATER RESOURCES RESEARCH
- Water demand forecasting in Umm Al-Quwain using the constant rate model
- (2010) Mohamed M. Mohamed et al. DESALINATION
- Urban water demand forecasting based on HP filter and fuzzy neural network
- (2010) Wu Li et al. JOURNAL OF HYDROINFORMATICS
- Predictive models for forecasting hourly urban water demand
- (2010) Manuel Herrera et al. JOURNAL OF HYDROLOGY
- Evaluating Water Demands under Climate Change and Transitions in the Urban Environment
- (2010) Austin S. Polebitski et al. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
- Identifying Prominent Explanatory Variables for Water Demand Prediction Using Artificial Neural Networks: A Case Study of Bangkok
- (2010) Mukand Singh Babel et al. WATER RESOURCES MANAGEMENT
- Space–time forecasting using soft geostatistics: a case study in forecasting municipal water demand for Phoenix, Arizona
- (2009) Seung-Jae Lee et al. STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
- Urban Water Demand Forecasting with a Dynamic Artificial Neural Network Model
- (2008) M. Ghiassi et al. JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT
- Freshwater consumption in Kuwait: analysis and forecasting
- (2008) Jasem M. Alhumoud JOURNAL OF WATER SUPPLY RESEARCH AND TECHNOLOGY-AQUA
Find Funding. Review Successful Grants.
Explore over 25,000 new funding opportunities and over 6,000,000 successful grants.
ExploreAsk a Question. Answer a Question.
Quickly pose questions to the entire community. Debate answers and get clarity on the most important issues facing researchers.
Get Started