Almanifi, Omair Rashed Abdulwareth and Ng, Jee Kwan and Anwar P. P., Abdul Majeed (2021) The classification of FTIR plastic bag spectra via label spreading and stacking. Mekatronika - Journal of Intelligent Manufacturing & Mechatronics, 3 (2). pp. 70-76. ISSN 2637-0883. (Published)
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Abstract
Whereas plastics are a group of the most useful materials, widely used in all walks of life, the plastic waste that is produced daily poses a great threat towards wildlife and the planet as a whole. The use of biodegradable plastics is an important step in combating the plastic crisis. FTIR spectroscopy is a non-destructive method used for identifying different types of materials, however interpreting spectra produced by such spectrometers is both susceptible to human error, and time-consuming, not to mention that the industry suffers from a great of specialists, in the field of spectroscopy. Utilising machine learning as a method of filling the mentioned issue is suggested by this paper. Four pipelines were investigated, consisting of two machine learning algorithms, a stacked model that stacks the KNN, SVM and RF algorithms together, and Label spreading, as well as two different dimensionality reduction methods namely; SVD and UMAP. The pipelines studied seemed to show great predictivity at 100% classification accuracy acquired by the SVD-Stacked pipeline when data was sampled using an Agilent Cary 660 FTIR Spectrometer, and 99.18% by the same model when IDIR BP10 spectrometer was employed for sampling instead. The semi-supervised learning model (Label Spreading) seemed to achieve close enough accuracy at 99.82% in the case of the former dataset, and 97.54% for the latter, at a labelling rate of only 10% of the full datasets.
| Item Type: | Article |
|---|---|
| Uncontrolled Keywords: | FTIR; Spectroscopy; Machine learning; Semisupervised learning; Plastic |
| Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TS Manufactures |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Manufacturing and Mechatronic Engineering Technology |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 09 May 2022 08:00 |
| Last Modified: | 09 May 2022 08:00 |
| URI: | http://umpir.ump.edu.my/id/eprint/34001 |
| Download Statistic: | View Download Statistics |
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