Choong, Chun Sern and Ahmad Fakhri, Ab. Nasir and Muhammad Aizzat, Zakaria and Anwar P. P., Abdul Majeed and Mohd Azraai, Mohd Razman (2020) Pallet-level classification using principal component analysis in ensemble learning model. Mekatronika - Journal of Intelligent Manufacturing & Mechatronics, 2 (1). pp. 23-27. ISSN 2637-0883. (Published)
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Abstract
In this paper, we present a machine learning pipeline to solve a multiclass classification of radio frequency identification (RFID) signal strength. The goal is to identify ten pallet levels using nine statistical features derived from RFID signals and four various ensemble learning classification models. The efficacy of the models was evaluated by considering features that were dimensionally reduced via Principal Component Analysis (PCA) and original features. It was shown that the PCA reduced features could provide a better classification accuracy of the pallet levels in comparison to the selection of all features via Extra Tree and Random Forest models.
| Item Type: | Article |
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| Uncontrolled Keywords: | Pallet-level; RFID; Ensemble Learning; Features Selection; RSSI |
| Subjects: | T Technology > TJ Mechanical engineering and machinery T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Faculty/Division: | Institute of Postgraduate Studies Faculty of Manufacturing and Mechatronic Engineering Technology |
| Depositing User: | Mrs Norsaini Abdul Samat |
| Date Deposited: | 01 Apr 2022 07:26 |
| Last Modified: | 01 Apr 2022 07:26 |
| URI: | http://umpir.ump.edu.my/id/eprint/33608 |
| Download Statistic: | View Download Statistics |
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