Tuning ANN Hyperparameters for Forecasting Drinking Water Demand

Tuning ANN Hyperparameters for Forecasting Drinking Water Demand

The evolution of smart water grids leads to new Big Data challenges boosting the development and application of Machine Learning techniques to support efficient and sustainable drinking water management. These powerful techniques rely on hyperparameters making the models’ tuning a tricky and crucial...

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Bibliographic Details
Main Authors: Andrea Menapace, Ariele Zanfei, Maurizio Righetti
Format: Article
Language:English
Published: MDPI AG 2021-05-01
Series:Applied Sciences
Subjects:
artificial neural networks
drinking water consumption
machine learning
grid search hyperparameters
short-term forecasting
tuning analysis
Online Access:https://www.mdpi.com/2076-3417/11/9/4290

Internet

https://www.mdpi.com/2076-3417/11/9/4290

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