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eISSN: 2581-9615 || CODEN: WJARAI || Impact Factor 8.2 ||  CrossRef DOI

Research and review articles are invited for publication in April 2026 (Volume 30, Issue 1) Submit manuscript

Classification of pH scale based on machine learning approaches

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Sasmita Kumari Nayak *

Computer Science and Engineering, Centurion University of Technology and Management, Odisha, India.
 
Review Article
World Journal of Advanced Research and Reviews, 2024, 21(01), 235-239
Article DOI: 10.30574/wjarr.2024.21.1.0014
DOI url: https://doi.org/10.30574/wjarr.2024.21.1.0014
 
Received on 22 November 2023; revised on 01 January 2024; accepted on 03 January 2024
 
This paper provides a demonstration of the idea for a microfluidic, which is based on dry chemicals, stable, and semi-quantitative assay using a larger dataset with a variety of conditions. An optical method is used to measure the color change of pH paper. In order to support the claim and provide evidence, this paper will specifically explore the parameters of an intelligent colorimetric test that satisfies the ASSURED standards. All the time it measures by using traditional manual method. Our goal in this study was to gather objective data by using Red, Green, and Blue values to represent the pH change of the paper. The system under investigation is an intelligent image-based system that performs automatic paper-based colorimetric tests in real-time. This paper classifies the pH scale by using machine learning models.
 
Image processing; Feature Extraction; pH paper image data; Machine Learning; KNN; Decision Tree; Random Forest.
 
https://wjarr.com/sites/default/files/fulltext_pdf/WJARR-2024-0014.pdf

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Sasmita Kumari Nayak. Classification of pH scale based on machine learning approaches. World Journal of Advanced Research and Reviews, 2024, 21(1), 235-239. Article DOI: https://doi.org/10.30574/wjarr.2024.21.1.0014

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