Work

Streamflow Forecasting Based on PatchTST, LSTM, and Ensemble Learning Approaches

Year: 2026

Type: article

Source: Water Resources Management

DOI: 10.1007/s11269-025-04397-y

Authors: Hajar Feizi, Mohammad Taghi Sattari

Institutions: Khazar University, University of Tabriz

Language: English

Topic: Hydrological Forecasting Using AI

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDGs: Climate action, Clean water and sanitation

Open Access status: green

OpenAlex ID: W7118123772

FWCI: 12.82

Cites: 27

Cited by: 8

Related to: 10