Classifying Nitrate in Aqueous Solution Using Supervised Machine Learning Based on Spectroscopic Technique

We demonstrate the classification of nitrate concentration in mixed solution based on spectroscopy measurements. Dimensionality reduction techniques and supervised machine learning classifiers were employed where the PCA-SVM model outperforms other models with 97.8% accuracy.

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Bibliographic Details
Published in2022 Conference on Lasers and Electro-Optics Pacific Rim (CLEO-PR) pp. 1 - 2
Main Authors Sulaiman, Rozita, Azeman, Nur Hidayah, Ahmad Nazri, Nur Afifah, Abu Bakar, Mohd Hafiz, Masran, Athiyah Sakinah, A Bakar, Ahmad Ashrif
Format Conference Proceeding
LanguageEnglish
Published IEEE 31.07.2022
Subjects
Biomedical measurement
Ions
Measurement by laser beam
Particle beam optics
Principal component analysis
Spectroscopy
Support vector machines
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Summary:We demonstrate the classification of nitrate concentration in mixed solution based on spectroscopy measurements. Dimensionality reduction techniques and supervised machine learning classifiers were employed where the PCA-SVM model outperforms other models with 97.8% accuracy.
DOI:10.1109/CLEO-PR62338.2022.10432468