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AI for enhanced water quality data imputation: a deep learning perspective

Year: 2025

Type: article

Abstract: Our proposed framework suggests the mitigations of limitations of traditional imputation models via incorporation of novel concepts such as spatial–temporal datasets, dynamic ensemble modelling and I/O aware mechanisms.

Source: Environmental Science Advances

DOI: 10.1039/d4va00367e

Authors: Ishan Prasad Banjara, Suman Poudel, Kalam Pariyar, Deepesh Upreti, Antigoni Zafeirakou, Shukra Raj Paudel

Institutions: Tribhuvan University, Institute of Engineering, Pulchowk Campus, Aristotle University of Thessaloniki

Language: English

Topic: Hydrological Forecasting Using AI

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDG: Clean water and sanitation

Open Access status: diamond

OpenAlex ID: W4409215349

FWCI: 2.852

Cites: 30

Cited by: 10

Related to: 10