Modelling residential water consumers’ behaviors by feature selection and feature weighting.

Andrea Cominola, Matteo Giuliani, Dario Piga, Andrea Castelletti, Andrea Emilio Rizzoli, Martin Anda

Thursday 2 july 2015

11:45 - 12:00h at North America (level 0)

Themes: (T) Special session, (ST) FP7 ICT and water

Parallel session: 11I. Special session: FP7 ICT and water

Identifying the most relevant determinants of water consuming or saving behaviors at the household level is key to building mathematical models that predict urban water demand variability in space and time and to explore the effects of different Water Demand Management Strategies for the residential sector. This work contributes a novel approach based on feature selection and feature weighting to model the single-user consumption behavior at the household level. A two-step procedure consisting of the extraction of the most relevant determinants of users’ consumption and the identification of a predictive model of water consumers’ profile is proposed and tested on a real case study. Results show the effectiveness of the proposed method in capturing the influence of candidate determinants on residential water consumption, as well as in attaining sufficiently accurate predictions of users’ consumption profiles, which constitutes essential information to support residential water demand management.