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Committee Machines for Hourly Water Demand Forecasting in Water Supply Systems
Joint Authors
Izquierdo, Joaquín
Brentan, B. M.
Luvizotto, E.
Ambrosio, Julia K.
Herrera, Manuel
Ribeiro, Lubienska
Source
Mathematical Problems in Engineering
Issue
Vol. 2019, Issue 2019 (31 Dec. 2019), pp.1-11, 11 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2019-01-08
Country of Publication
Egypt
No. of Pages
11
Main Subjects
Abstract EN
Prediction models have become essential for the improvement of decision-making processes in public management and, particularly, for water supply utilities.
Accurate estimation often needs to solve multimeasurement, mixed-mode, and space-time problems, typical of many engineering applications.
As a result, accurate estimation of real world variables is still one of the major problems in mathematical approximation.
Several individual techniques have shown very good estimation abilities.
However, none of them are free from drawbacks.
This paper faces the challenge of creating accurate water demand predictive models at urban scale by using so-called committee machines, which are ensemble frameworks of single machine learning models.
The proposal is able to combine models of varied nature.
Specifically, this paper analyzes combinations of such techniques as multilayer perceptrons, support vector machines, extreme learning machines, random forests, adaptive neural fuzzy inference systems, and the group method for data handling.
Analyses are checked on two water demand datasets from Franca (Brazil).
As an ensemble tool, the combined response of a committee machine outperforms any single constituent model.
American Psychological Association (APA)
Ambrosio, Julia K.& Brentan, B. M.& Herrera, Manuel& Luvizotto, E.& Ribeiro, Lubienska& Izquierdo, Joaquín. 2019. Committee Machines for Hourly Water Demand Forecasting in Water Supply Systems. Mathematical Problems in Engineering،Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1200842
Modern Language Association (MLA)
Ambrosio, Julia K.…[et al.]. Committee Machines for Hourly Water Demand Forecasting in Water Supply Systems. Mathematical Problems in Engineering No. 2019 (2019), pp.1-11.
https://search.emarefa.net/detail/BIM-1200842
American Medical Association (AMA)
Ambrosio, Julia K.& Brentan, B. M.& Herrera, Manuel& Luvizotto, E.& Ribeiro, Lubienska& Izquierdo, Joaquín. Committee Machines for Hourly Water Demand Forecasting in Water Supply Systems. Mathematical Problems in Engineering. 2019. Vol. 2019, no. 2019, pp.1-11.
https://search.emarefa.net/detail/BIM-1200842
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1200842