Related references
Note: Only part of the references are listed.Forecasting Residential Water Consumption in California: Rethinking Model Selection
Steven Buck et al.
WATER RESOURCES RESEARCH (2020)
Disturbance Extraction for Burst Detection in Water Distribution Networks Using Pressure Measurements
Weirong Xu et al.
WATER RESOURCES RESEARCH (2020)
Burst Detection in District Metering Areas Using Deep Learning Method
Xiaoting Wang et al.
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2020)
Criteria for classifying forecasting methods
Tim Januschowski et al.
INTERNATIONAL JOURNAL OF FORECASTING (2020)
The M4 Competition: 100,000 time series and 61 forecasting methods
Spyros Makridakis et al.
INTERNATIONAL JOURNAL OF FORECASTING (2020)
Applying human mobility and water consumption data for short-term water demand forecasting using classical and machine learning models
Kamil Smolak et al.
URBAN WATER JOURNAL (2020)
Energetic optimization and evaluation of a drinking water pumping system: application at the Rassauta station
Bouach Ahcene et al.
WATER SUPPLY (2019)
Evolutionary Deep Learning with Extended Kalman Filter for Effective Prediction Modeling and Efficient Data Assimilation
Qiao Li et al.
JOURNAL OF COMPUTING IN CIVIL ENGINEERING (2019)
Monitoring Support for Water Distribution Systems based on Pressure Sensor Data
Caspar V. C. Geelen et al.
WATER RESOURCES MANAGEMENT (2019)
Predicting water demand: a review of the methods employed and future possibilities
Gustavo de Souza Groppo et al.
WATER SUPPLY (2019)
Comparison of stochastic and machine learning methods for multi-step ahead forecasting of hydrological processes
Georgia Papacharalampous et al.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT (2019)
Forecasting Hourly Water Demands With Seasonal Autoregressive Models for Real-Time Application
Jinduan Chen et al.
WATER RESOURCES RESEARCH (2018)
Short-Term Water Demand Forecast Based on Deep Learning Method
Guancheng Guo et al.
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2018)
Real-Time Burst Detection in District Metering Areas in Water Distribution System Based on Patterns of Water Demand with Supervised Learning
Pingjie Huang et al.
WATER (2018)
Forecasting at Scale
Sean J. Taylor et al.
AMERICAN STATISTICIAN (2018)
Pipe network leak detection: comparison between statistical and machine learning techniques
J. C. van der Walt et al.
URBAN WATER JOURNAL (2018)
Water demand forecasting: review of soft computing methods
Iman Ghalehkhondabi et al.
ENVIRONMENTAL MONITORING AND ASSESSMENT (2017)
Leakage Detection and Estimation Algorithm for Loss Reduction in Water Piping Networks
Kazeem B. Adedeji et al.
WATER (2017)
Detecting anomalies in water distribution networks using EPR modelling paradigm
Daniele Laucelli et al.
JOURNAL OF HYDROINFORMATICS (2016)
Improving the rapidity of responses to pipe burst in water distribution systems: a comparison of statistical process control methods
Donghwi Jung et al.
JOURNAL OF HYDROINFORMATICS (2015)
Automated Detection of Pipe Bursts and Other Events in Water Distribution Systems
Michele Romano et al.
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2014)
Geostatistical techniques for approximate location of pipe burst events in water distribution systems
Michele Romano et al.
JOURNAL OF HYDROINFORMATICS (2013)
Leakage fault detection in district metered areas of water distribution systems
D. G. Eliades et al.
JOURNAL OF HYDROINFORMATICS (2012)
Burst Detection in Water Networks Using Principal Component Analysis
C. V. Palau et al.
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2012)
Comparison of multiple linear and nonlinear regression, autoregressive integrated moving average, artificial neural network, and wavelet artificial neural network methods for urban water demand forecasting in Montreal, Canada
Jan Adamowski et al.
WATER RESOURCES RESEARCH (2012)
Novelty detection for time series data analysis in water distribution systems using support vector machines
Stephen R. Mounce et al.
JOURNAL OF HYDROINFORMATICS (2011)
Predictive models for forecasting hourly urban water demand
Manuel Herrera et al.
JOURNAL OF HYDROLOGY (2010)
Development and Verification of an Online Artificial Intelligence System for Detection of Bursts and Other Abnormal Flows
S. R. Mounce et al.
JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2010)
Short-term municipal water demand forecasting
J Bougadis et al.
HYDROLOGICAL PROCESSES (2005)
Leakage detection in water pipe networks using a Bayesian probabilistic framework
Z Poulakis et al.
PROBABILISTIC ENGINEERING MECHANICS (2003)
Forecasting operational demand for an urban water supply zone
SL Zhou et al.
JOURNAL OF HYDROLOGY (2002)
A neural network approach to burst detection
SR Mounce et al.
WATER SCIENCE AND TECHNOLOGY (2002)
Statistical modeling: The two cultures
L Breiman
STATISTICAL SCIENCE (2001)
The theta model: a decomposition approach to forecasting
V Assimakopoulos et al.
INTERNATIONAL JOURNAL OF FORECASTING (2000)
Forecasting daily urban water demand: a case study of Melbourne
SL Zhou et al.
JOURNAL OF HYDROLOGY (2000)