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Gene Expression Programming Coupled with Unsupervised Learning: A Two-Stage Learning Process in Multi-Scale, Short-Term Water Demand Forecasts Shabani, Sina; Candelieri, Antonio; Archetti, Francesco; Naser, Gholamreza

Abstract

This article proposes a new general approach in short-term water demand forecasting based on a two-stage learning process that couples time-series clustering with gene expression programming (GEP). The approach was tested on the real life water demand data of the city of Milan, in Italy. Moreover, multi-scale modeling using a series of head-time was deployed to investigate the optimum temporal resolution under study. Multi-scale modeling was performed based on rearranging hourly based patterns of water demand into 3, 6, 12, and 24 h lead times. Results showed that GEP should receive more attention among the emerging nonlinear modelling techniques if coupled with unsupervised learning algorithms in detailed spherical k-means.

Item Metadata

Title
Gene Expression Programming Coupled with Unsupervised Learning: A Two-Stage Learning Process in Multi-Scale, Short-Term Water Demand Forecasts
Creator
Shabani, Sina; Candelieri, Antonio; Archetti, Francesco; Naser, Gholamreza
Publisher
Multidisciplinary Digital Publishing Institute
Date Issued
2018-02-02
Description
This article proposes a new general approach in short-term water demand forecasting based on a two-stage learning process that couples time-series clustering with gene expression programming (GEP). The approach was tested on the real life water demand data of the city of Milan, in Italy. Moreover, multi-scale modeling using a series of head-time was deployed to investigate the optimum temporal resolution under study. Multi-scale modeling was performed based on rearranging hourly based patterns of water demand into 3, 6, 12, and 24 h lead times. Results showed that GEP should receive more attention among the emerging nonlinear modelling techniques if coupled with unsupervised learning algorithms in detailed spherical k-means.
Subject
Short-term water demand forecasting; Multi-scale modeling; Gene expression programming; Clustering; Average mutual information
Genre
Article
Type
Text
Language
eng
Date Available
2019-07-03
Provider
Vancouver : University of British Columbia Library
Rights
CC BY 4.0
DOI
10.14288/1.0379718
URI
http://hdl.handle.net/2429/70885
Affiliation
Applied Science, Faculty of; Non UBC; Engineering, School of (Okanagan)
Citation
Water 10 (2): 142 (2018)
Publisher DOI
10.3390/w10020142
Peer Review Status
Reviewed
Scholarly Level
Faculty
Rights URI
https://creativecommons.org/licenses/by/4.0/
Aggregated Source Repository
DSpace

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CC BY 4.0