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Journals / Journal of International Environmental Application and Science / 2026 / Volume: 19 Issue: 2

Design and Implementation of A Graphical User Interface for Outlier Data Analysis: A Case Study on the Yesilirmak River

Eda Göz(ANKARA ÜNİVERSİTESİ)0000-0002-3111-9042
Zübeyde Zengül(HITIT UNIVERSITY, FACULTY OF ENGINEERING)0000-0001-5851-1418
Erdal Karadurmuş(HITIT UNIVERSITY, FACULTY OF ENGINEERING)0000-0002-1836-5126
Mehmet Yüceer(INONU UNIVERSITY, FACULTY OF ENGINEERING)0000-0002-2648-3931
Pages
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Publication Date
2024-06-30
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

It was observed that the median algorithm removed the most data points among the outlier data-removal methods.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:Water quality control, especially in large-scale monitoring regions or networks, requires easy and automatic processes for detecting potential outliers in a reproducible manner.
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Key Findings & Data:This study focuses on removing outlier values from a dataset collected by an online monitoring station on the Yeşilırmak River between 2007 and 2009.
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Conclusion & Impact:It was observed that the median algorithm removed the most data points among the outlier data-removal methods.
🔬Design:Modeling & Simulation
📍Scope:2007 Verileri
⚙️Variables:River water quality data · outlier detection · statistical methods

Abstract

Water quality control, especially in large-scale monitoring regions or networks, requires easy and automatic processes for detecting potential outliers in a reproducible manner. This study focuses on removing outlier values from a dataset collected by an online monitoring station on the Yeşilırmak River between 2007 and 2009. Seven different parameters were evaluated: dissolved oxygen (luminescence dissolved oxygen, LDO), temperature, pH, conductivity, total organic carbon (TOC), nitrate nitrogen (NO3-N), and ammonium nitrogen (NH4-N). Five methods – median, mean, Grubbs’, generalized extreme studentized deviate (GESD), and interquartile range (IQR) – were used for outlier removal. The developed models were integrated into a graphical user interface (GUI) in the MATLAB environment, facilitating practical and easy access. This study enables users to input any dataset into the software and remove outlier values using various methods in a few steps, thus preparing the data for modeling studies. It was observed that the median algorithm removed the most data points among the outlier data-removal methods.

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Cite This Article

Göz, E., Zengül, Z., Karadurmuş, E., Yüceer, M. (2024). Design and Implementation of A Graphical User Interface for Outlier Data Analysis: A Case Study on the Yesilirmak River. Journal of International Environmental Application and Science, Volume: 19 Issue: 2. https://ajindex.com/articles/1112230

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