Tailoring Seasonal Time Series Models to Forecast Short-Term Water Demand-Reference-Cited by-同舟云学术

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Tailoring Seasonal Time Series Models to Forecast Short-Term Water Demand

Published:2016-03 Issue:3 Volume:142 Page:04015067
ISSN:0733-9496
Container-title:Journal of Water Resources Planning and Management
language:en
Short-container-title:J. Water Resour. Plann. Manage.

Author:

Arandia Ernesto¹,Ba Amadou²,Eck Bradley²,McKenna Sean³

Affiliation:

1. Research Scientist, IBM Research, IBM Technology Campus Bldg. 3, Damastown, Dublin 15, Ireland (corresponding author).

2. Research Scientist, IBM Research, IBM Technology Campus Bldg. 3, Damastown, Dublin 15, Ireland.

3. Senior Manager, IBM Research, IBM Technology Campus Bldg. 3, Damastown, Dublin 15, Ireland.

Publisher

American Society of Civil Engineers (ASCE)

Subject

Management, Monitoring, Policy and Law,Water Science and Technology,Geography, Planning and Development,Civil and Structural Engineering

Link

http://ascelibrary.org/doi/pdf/10.1061/%28ASCE%29WR.1943-5452.0000591

Reference52 articles.

1. A wavelet neural network conjunction model for groundwater level forecasting

2. 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

3. Water Consumption Prediction of Istanbul City by Using Fuzzy Logic Approach

4. A short-term, pattern-based model for water-demand forecasting

5. Short-Term Forecasting for Urban Water Consumption

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