Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Eine Plattform für die Wissenschaft: Bauingenieurwesen, Architektur und Urbanistik
Clustering and Support Vector Regression for Water Demand Forecasting and Anomaly Detection
This paper presents a completely data-driven and machine-learning-based approach, in two stages, to first characterize and then forecast hourly water demand in the short term with applications of two different data sources: urban water demand (SCADA data) and individual customer water consumption (AMR data). In the first case, reliable forecasting can be used to optimize operations, particularly the pumping schedule, in order to reduce energy-related costs, while in the second case, the comparison between forecast and actual values may support the online detection of anomalies, such as smart meter faults, fraud or possible cyber-physical attacks. Results are presented for a real case: the water distribution network in Milan.
Clustering and Support Vector Regression for Water Demand Forecasting and Anomaly Detection
This paper presents a completely data-driven and machine-learning-based approach, in two stages, to first characterize and then forecast hourly water demand in the short term with applications of two different data sources: urban water demand (SCADA data) and individual customer water consumption (AMR data). In the first case, reliable forecasting can be used to optimize operations, particularly the pumping schedule, in order to reduce energy-related costs, while in the second case, the comparison between forecast and actual values may support the online detection of anomalies, such as smart meter faults, fraud or possible cyber-physical attacks. Results are presented for a real case: the water distribution network in Milan.
Clustering and Support Vector Regression for Water Demand Forecasting and Anomaly Detection
Antonio Candelieri (Autor:in)
2017
Aufsatz (Zeitschrift)
Elektronische Ressource
Unbekannt
Metadata by DOAJ is licensed under CC BY-SA 1.0
Support Vector Machine Regression for project control forecasting
| Elsevier | 2014
Support Vector Machine Regression for project control forecasting
| Online Contents | 2014
Support Vector Machine Regression for project control forecasting
| British Library Online Contents | 2014
Forecasting urban water demand: A meta-regression analysis
| Online Contents | 2016
Forecasting urban water demand: A meta-regression analysis
| Online Contents | 2016