ID:
publications-2679
Type:
Peer reviewed articles
Year:
2019
Authors:
Antonio Candelieri, Ilaria Giordani, Francesco Archetti, Konstantin Barkalov, Iosif Meyerov, Alexey Polovinkin, Alexander Sysoyev, Nikolai Zolotykh
Title:
Tuning hyperparameters of a SVM-based water demand forecasting system through parallel global optimization
Venue/Journal:
Computers & Operations Research
DOI:
10.1016/j.cor.2018.01.013
Research type:
Data Management & Analytics
Water System:
Natural Water Bodies
Technical Focus:
Abstract:
No abstract available
Link with Projects:
690900
Link with Tools:
Related policies:
ID:
