Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models
Joint Authors
Izquierdo, Joaquín
Brentan, B. M.
Meirelles, G.
Herrera, M.
Luvizotto, E.
Source
Mathematical Problems in Engineering
Issue
Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2017-12-18
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Abstract EN
Operational and economic aspects of water distribution make water demand forecasting paramount for water distribution systems (WDSs) management.
However, water demand introduces high levels of uncertainty in WDS hydraulic models.
As a result, there is growing interest in developing accurate methodologies for water demand forecasting.
Several mathematical models can serve this purpose.
One crucial aspect is the use of suitable predictive variables.
The most used predictive variables involve weather and social aspects.
To improve the interrelation knowledge between water demand and various predictive variables, this study applies three algorithms, namely, classical Principal Component Analysis (PCA) and machine learning powerful algorithms such as Self-Organizing Maps (SOMs) and Random Forest (RF).
We show that these last algorithms help corroborate the results found by PCA, while they are able to unveil hidden features for PCA, due to their ability to cope with nonlinearities.
This paper presents a correlation study of three district metered areas (DMAs) from Franca, a Brazilian city, exploring weather and social variables to improve the knowledge of residential demand for water.
For the three DMAs, temperature, relative humidity, and hour of the day appear to be the most important predictive variables to build an accurate regression model.
American Psychological Association (APA)
Brentan, B. M.& Meirelles, G.& Herrera, M.& Luvizotto, E.& Izquierdo, Joaquín. 2017. Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models. Mathematical Problems in Engineering،Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1191353
Modern Language Association (MLA)
Brentan, B. M.…[et al.]. Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models. Mathematical Problems in Engineering No. 2017 (2017), pp.1-10.
https://search.emarefa.net/detail/BIM-1191353
American Medical Association (AMA)
Brentan, B. M.& Meirelles, G.& Herrera, M.& Luvizotto, E.& Izquierdo, Joaquín. Correlation Analysis of Water Demand and Predictive Variables for Short-Term Forecasting Models. Mathematical Problems in Engineering. 2017. Vol. 2017, no. 2017, pp.1-10.
https://search.emarefa.net/detail/BIM-1191353
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1191353