The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis

Selda Palabıyık

doi:10.35229/jaes.1813761

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The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis

Abstract

This paper showcases the evolution of research in machine learning (ML)-based water quality index and water quality forecasting through a multi-database bibliometric and content analytical framework for the period of 2010 to 2025. The data were integrated in R through the use of bibliometrix as well as Biblioshiny, and duplicate records were removed to obtain a comprehensive data set suitable for citation and network analysis. The descriptive study combined traditional indicators, annual scientific output, author/source impact indexes, collaboration networks, conceptual mapping, and thematic evolution to identify the intellectual pillars of the field and its emerging topics. The results show a highly collaborative and growing research environment with increasing methodological complexity. There is distinctly apparent shift in the methods of ML toward deep and ensemble techniques over the recent few years. Further results of text mining and content analysis show that parameter complexity is linking very closely to model selection, which supports the use of both highly nonlinear, biochemical sophisticated architectures variables and more interpretable methods for stable physical indicators. This paper finds that explainability has become of emerging importance together with reproducibility and decision-oriented modeling in long-term water quality management strategies, into which the domain is rapidly integrating.

Keywords

Water Quality Index (WQI, Bibliometrics, Machine Learning (ML), Artificial Intelligence (AI)

Makine Öğrenimi Tabanlı Su Kalitesi Endeksi (WQI) Tahminine İlişkin Araştırmaların Gelişimi: Bibliyometrik Analiz

Abstract

Bu makale, 2010-2025 dönemi için çoklu veritabanı bibliyometrik ve içerik analitik çerçevesi aracılığıyla makine öğrenimi (MÖ) tabanlı su kalitesi endeksi ve su kalitesi tahminine yönelik araştırmaların gelişimini göstermektedir. Veriler, bibliometrix ve Biblioshiny kullanılarak R'ye entegre edilmiş ve alıntı ve ağ analizi için uygun kapsamlı bir veri seti elde etmek amacıyla yinelenen kayıtlar kaldırılmıştır. Tanımlayıcı çalışma, geleneksel göstergeler, yıllık bilimsel çıktı, yazar/kaynak etki endeksleri, işbirliği ağları, kavramsal haritalama ve tematik evrimi bir araya getirerek, bu alanın entelektüel temellerini ve ortaya çıkan konularını belirlemiştir. Sonuçlar, metodolojik karmaşıklığın arttığı, işbirliğine dayalı ve büyüyen bir araştırma ortamını göstermektedir. Son birkaç yılda, MÖ yöntemlerinde derin ve toplu tekniklere doğru belirgin bir geçiş olduğu görülmektedir. Metin madenciliği ve içerik analizinin diğer sonuçları, parametre karmaşıklığının model seçimiyle çok yakından bağlantılı olduğunu göstermektedir. Bu da, hem son derece doğrusal olmayan biyokimyasal sofistike mimari değişkenlerin hem de daha yorumlanabilir yöntemlerin istikrarlı fiziksel göstergeler için kullanılmasını desteklemektedir. Bu makale, uzun vadeli su kalitesi yönetim stratejisinde açıklanabilirliğin, tekrarlanabilirlik ve karar odaklı modelleme ile birlikte giderek önem kazandığını ve bu alanın hızla entegre olduğunu ortaya koymaktadır.

Keywords

Su Kalitesi İndeksi (WQI), Bibliyometri, Makine Öğrenmesi (MÖ), Yapay zeka (YZ)

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Details

Primary Language

English

Subjects

Ecology (Other)

Journal Section

Research Article

Authors

Selda Palabıyık ^*
0000-0001-6457-5733
Türkiye

Publication Date

March 19, 2026

Submission Date

October 31, 2025

Acceptance Date

February 19, 2026

Published in Issue

Year 2026 Number: 2026

DOI

https://doi.org/10.35229/jaes.1813761

IZ

https://izlik.org/JA84WC67AP

APA

Palabıyık, S. (2026). The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis. Journal of Anatolian Environmental and Animal Sciences, 2026. https://doi.org/10.35229/jaes.1813761

AMA

1.Palabıyık S. The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis. JAES. 2026;(2026). doi:10.35229/jaes.1813761

Chicago

Palabıyık, Selda. 2026. “The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis”. Journal of Anatolian Environmental and Animal Sciences, nos. 2026. https://doi.org/10.35229/jaes.1813761.

EndNote

Palabıyık S (March 1, 2026) The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis. Journal of Anatolian Environmental and Animal Sciences 2026

IEEE

[1]S. Palabıyık, “The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis”, JAES, no. 2026, Mar. 2026, doi: 10.35229/jaes.1813761.

ISNAD

Palabıyık, Selda. “The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis”. Journal of Anatolian Environmental and Animal Sciences. 2026 (March 1, 2026). https://doi.org/10.35229/jaes.1813761.

JAMA

1.Palabıyık S. The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis. JAES. 2026. doi:10.35229/jaes.1813761.

MLA

Palabıyık, Selda. “The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis”. Journal of Anatolian Environmental and Animal Sciences, no. 2026, Mar. 2026, doi:10.35229/jaes.1813761.

Vancouver

1.Selda Palabıyık. The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis. JAES. 2026 Mar. 1;(2026). doi:10.35229/jaes.1813761

EBSCOHost Scilit CABI

JAES/AAS-Journal of Anatolian Environmental and Animal Sciences/Anatolian Academic Sciences&Anadolu Çevre ve Hayvancılık Dergisi/Anadolu Akademik Bilimler-AÇEH/AAS

The Development of Research on Machine Learning-Based Water Quality Index (WQI) Prediction: A Bibliometric Analysis

Abstract

Keywords

Makine Öğrenimi Tabanlı Su Kalitesi Endeksi (WQI) Tahminine İlişkin Araştırmaların Gelişimi: Bibliyometrik Analiz

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