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Pallet-level classification using principal component analysis in ensemble learning model

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 m...

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Bibliographic Details
Main Authors: Choong, Chun Sern, Ahmad Fakhri, Ab. Nasir, Muhammad Aizzat, Zakaria, Anwar P. P., Abdul Majeed, Mohd Azraai, Mohd Razman
Format: Article
Language:English
Published: Penerbit UMP 2020
Subjects:
TJ Mechanical engineering and machinery
TK Electrical engineering. Electronics Nuclear engineering
Online Access:http://umpir.ump.edu.my/id/eprint/33608/1/Pallet%20level%20classification%20using%20principal%20component%20analysis.pdf
http://umpir.ump.edu.my/id/eprint/33608/
https://doi.org/10.15282/mekatronika.v2i1.6720
https://doi.org/10.15282/mekatronika.v2i1.6720
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Internet

http://umpir.ump.edu.my/id/eprint/33608/1/Pallet%20level%20classification%20using%20principal%20component%20analysis.pdf
http://umpir.ump.edu.my/id/eprint/33608/
https://doi.org/10.15282/mekatronika.v2i1.6720
https://doi.org/10.15282/mekatronika.v2i1.6720

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