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Trends and gaps in ai‐driven predictive models for coastal water quality: A bibliometric study

Year: 2025

Type: article

Study design: Systematic Review

Source: Springer Link (Chiba Institute of Technology)

DOI: 10.1051/bioconf/202518804004/pdf

Author: Sigit Setiawan

Language: English

Topic: Water Quality Monitoring Technologies

Subfield: Water Science and Technology

Field: Environmental Science

Domain: Physical Sciences

SDG: Clean water and sanitation

Open Access status: closed

OpenAlex ID: W7127159336

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