Work

Predicting Chlorophyll-a Concentrations in the World’s Largest Lakes Using Kolmogorov-Arnold Networks

Year: 2025

Type: article

Source: Environmental Science & Technology

DOI: 10.1021/acs.est.4c11113

Authors: Mohammad Javad Saravani, Roohollah Noori, Changhyun Jun, Dongkyun Kim, Sayed M. Bateni, Peiman Kianmehr, Richard Iestyn Woolway

Institutions: University of Tehran, Korea University, Hongik University, University of Hawaiʻi at Mānoa, University of South Africa, American University in Dubai, Bangor University

Language: English

Topic: Hydrological Forecasting Using AI

Subfield: Environmental Engineering

Field: Environmental Science

Domain: Physical Sciences

SDG: Clean water and sanitation

Open Access status: closed

OpenAlex ID: W4406474170

FWCI: 18.88

Cites: 57

Cited by: 81

Related to: 10