Classification of Different Recycled Rubber-Epoxy Composite Based on their Hardness Using Laser-Induced Breakdown Spectroscopy (LIBS) with Comparison Machine Learning Algorithms - HAL UNIV-PARIS8 - open access Access content directly
Journal Articles MDPI Year : 2023

Classification of Different Recycled Rubber-Epoxy Composite Based on their Hardness Using Laser-Induced Breakdown Spectroscopy (LIBS) with Comparison Machine Learning Algorithms

Abstract

This paper aims toward the successful detection of harmful materials in a substance by integrating machine learning (ML) into laser-induced breakdown spectroscopy (LIBS). LIBS is used to distinguish five different synthetic polymers where eight different heavy material contents are also detected by LIBS. Each material intensity-wavelength graph is obtained and the dataset is constructed for classification by a machine learning (ML) algorithm. Seven popular machine learning algorithms are applied to the dataset which include eight different substances with their wavelength-intensity value. Machine learning algorithms are used to train the dataset, results are discussed and which classification algorithm is appropriate for this dataset is determined.
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Dates and versions

hal-04019384 , version 1 (08-03-2023)

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Vadi Su Yılmaz, Kemal Efe Eseller, Ozgur Aslan, Emin Bayraktar. Classification of Different Recycled Rubber-Epoxy Composite Based on their Hardness Using Laser-Induced Breakdown Spectroscopy (LIBS) with Comparison Machine Learning Algorithms. MDPI , 2023, ⟨10.3390/inventions8020054⟩. ⟨hal-04019384⟩
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