Work

From Deterministic to Probabilistic Forecasts of Water Demand

Year: 2024

Type: conference-paper

Abstract: This work presents the application of the MCP as the integrator of two NN-type models, to provide probabilistic forecasts of water demand within the frame of the WDSA 2024 Battle. The proposed approach allows assessing the probability distribution of future values of water demand conditional to the deterministic model forecasts.

DOI: 10.3390/engproc2024069122

Authors: Annalaura Gabriele, Daniela Biondi, Rudy Gargano, Ezio Todini

Institutions: Università degli studi di Cassino e del Lazio Meridionale, University of Calabria

Language: English

Topic: Hydrological Forecasting Using AI

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDG: Clean water and sanitation

Open Access status: gold

OpenAlex ID: W4402492480

FWCI: 1.103

Cites: 7

Cited by: 1

Related to: 10