Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group
Conferences > CLEOPR > 2022 > P_CTh13 > P_CTh13_01

Classifying Nitrate in Aqueous Solution using Supervised Machine Learning based on Spectroscopic Technique

Rozita Sulaiman, Nur Hidayah Azeman, Nur Afifah Ahmad Nazri, Mohd Hafiz Abu Bakar, Athiyah Sakinah Masran, and Ahmad Ashrif A Bakar

Not Accessible

Your library or personal account may give you access

Abstract

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.

© 2022 IEEE

PDF Article
More Like This
Entanglement-Enhanced Physical-Layer Classifier Using Supervised Machine Learning

Quntao Zhuang and Zheshen Zhang
FF1F.1 CLEO: QELS_Fundamental Science (CLEO:FS) 2019

Entanglement-Enhanced Physical-Layer Classifier Using Supervised Machine Learning

Quntao Zhuang and Zheshen Zhang
QTh6A.8 Quantum 2.0 (QUANTUM) 2020

Classification of urine components using supervised machine learning based on physical particle data retrieved by digital holographic microscopy

Yussef Hanna, Marlene Kallaß, Álvaro Barroso, Jürgen Schnekenburger, Klaus Brinker, and Björn Kemper
Th2A.5 Digital Holography and Three-Dimensional Imaging (DH) 2022

View More...
Select as filters
Select Topics Cancel
Top
       
© Copyright 2024 | Optica Publishing Group. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies.
Privacy | Terms of Use