4.7 Article

Predictive modeling framework accelerated by GPU computing for smart water grid data-driven analysis in near real-time

Related references

Note: Only part of the references are listed.
Article Environmental Sciences

Forecasting Residential Water Consumption in California: Rethinking Model Selection

Steven Buck et al.

WATER RESOURCES RESEARCH (2020)

Article Environmental Sciences

Disturbance Extraction for Burst Detection in Water Distribution Networks Using Pressure Measurements

Weirong Xu et al.

WATER RESOURCES RESEARCH (2020)

Article Engineering, Civil

Burst Detection in District Metering Areas Using Deep Learning Method

Xiaoting Wang et al.

JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2020)

Editorial Material Economics

Criteria for classifying forecasting methods

Tim Januschowski et al.

INTERNATIONAL JOURNAL OF FORECASTING (2020)

Article Economics

The M4 Competition: 100,000 time series and 61 forecasting methods

Spyros Makridakis et al.

INTERNATIONAL JOURNAL OF FORECASTING (2020)

Article Computer Science, Interdisciplinary Applications

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)

Article Engineering, Civil

Monitoring Support for Water Distribution Systems based on Pressure Sensor Data

Caspar V. C. Geelen et al.

WATER RESOURCES MANAGEMENT (2019)

Review Engineering, Environmental

Predicting water demand: a review of the methods employed and future possibilities

Gustavo de Souza Groppo et al.

WATER SUPPLY (2019)

Article Engineering, Environmental

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)

Article Environmental Sciences

Forecasting Hourly Water Demands With Seasonal Autoregressive Models for Real-Time Application

Jinduan Chen et al.

WATER RESOURCES RESEARCH (2018)

Article Engineering, Civil

Short-Term Water Demand Forecast Based on Deep Learning Method

Guancheng Guo et al.

JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2018)

Article Statistics & Probability

Forecasting at Scale

Sean J. Taylor et al.

AMERICAN STATISTICIAN (2018)

Article Water Resources

Pipe network leak detection: comparison between statistical and machine learning techniques

J. C. van der Walt et al.

URBAN WATER JOURNAL (2018)

Review Environmental Sciences

Water demand forecasting: review of soft computing methods

Iman Ghalehkhondabi et al.

ENVIRONMENTAL MONITORING AND ASSESSMENT (2017)

Article Environmental Sciences

Leakage Detection and Estimation Algorithm for Loss Reduction in Water Piping Networks

Kazeem B. Adedeji et al.

WATER (2017)

Article Computer Science, Interdisciplinary Applications

Detecting anomalies in water distribution networks using EPR modelling paradigm

Daniele Laucelli et al.

JOURNAL OF HYDROINFORMATICS (2016)

Article Computer Science, Interdisciplinary Applications

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)

Article Engineering, Civil

Automated Detection of Pipe Bursts and Other Events in Water Distribution Systems

Michele Romano et al.

JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2014)

Article Computer Science, Interdisciplinary Applications

Geostatistical techniques for approximate location of pipe burst events in water distribution systems

Michele Romano et al.

JOURNAL OF HYDROINFORMATICS (2013)

Article Computer Science, Interdisciplinary Applications

Leakage fault detection in district metered areas of water distribution systems

D. G. Eliades et al.

JOURNAL OF HYDROINFORMATICS (2012)

Article Engineering, Civil

Burst Detection in Water Networks Using Principal Component Analysis

C. V. Palau et al.

JOURNAL OF WATER RESOURCES PLANNING AND MANAGEMENT (2012)

Article Computer Science, Interdisciplinary Applications

Novelty detection for time series data analysis in water distribution systems using support vector machines

Stephen R. Mounce et al.

JOURNAL OF HYDROINFORMATICS (2011)

Article Engineering, Civil

Predictive models for forecasting hourly urban water demand

Manuel Herrera et al.

JOURNAL OF HYDROLOGY (2010)

Article Engineering, Civil

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)

Article Water Resources

Short-term municipal water demand forecasting

J Bougadis et al.

HYDROLOGICAL PROCESSES (2005)

Article Engineering, Mechanical

Leakage detection in water pipe networks using a Bayesian probabilistic framework

Z Poulakis et al.

PROBABILISTIC ENGINEERING MECHANICS (2003)

Article Engineering, Civil

Forecasting operational demand for an urban water supply zone

SL Zhou et al.

JOURNAL OF HYDROLOGY (2002)

Article Engineering, Environmental

A neural network approach to burst detection

SR Mounce et al.

WATER SCIENCE AND TECHNOLOGY (2002)

Article Computer Science, Artificial Intelligence

Random forests

L Breiman

MACHINE LEARNING (2001)

Article Statistics & Probability

Statistical modeling: The two cultures

L Breiman

STATISTICAL SCIENCE (2001)

Article Economics

The theta model: a decomposition approach to forecasting

V Assimakopoulos et al.

INTERNATIONAL JOURNAL OF FORECASTING (2000)

Article Engineering, Civil

Forecasting daily urban water demand: a case study of Melbourne

SL Zhou et al.

JOURNAL OF HYDROLOGY (2000)