id	author	title	date	pages	extension	mime	words	sentence	flesch	summary	cache	txt
fuelectenerg-12594	Hasan, Md Mahmudul; Islam, Md Nahidul; Khandaker, Sayma; Sulaiman, Norizam; Islam, Ashraful; Hossain, Mirza Mahfuj	ENSEMBLE-BASED MACHINE LEARNING MODELS FOR VEHICLE DRIVERS’ FATIGUE STATE DETECTION UTILIZING EEG SIGNALS	2024	16	.pdf	application/pdf	6765	404	52	Received March 26, 2024; revised July 05, 2024; accepted July 18, 2024 Corresponding author: Norizam Sulaiman Faculty of Electrical and Electronics Engineering Technology, Universiti Malaysia Pahang Al-Sultan Abdullah, Pahang 26600, Malaysia E-mail: norizam@umpsa.edu.my https://orcid.org/0009-0004-6865-3785 https://orcid.org/0000-0003-1552-0335 https://orcid.org/0009-0007-7621-3554 https://orcid.org/0000-0002-0625-2327 https://orcid.org/0009-0006-1157-5055 https://orcid.org/0009-0009-7391-5635 672 M. M. HASAN, M. N. ISLAM, S. KHANDAKER, N. SULAIMAN, A. ISLAM, M. M. HOSSAIN Key words: Fatigue state detection, EEG signal, Ensemble based classifier, RUSBoosted Decision Tree, Random Subspace Discriminant 1. INTRODUCTION The excessive frequency of highways catastrophes has led to socioeconomic problems that endanger both human beings and their belongings. [13] T. Tuncer, S. Dogan, F. Ertam, and A. Subasi, A dynamic center and multi threshold point based stable feature extraction network for driver fatigue detection utilizing EEG signals, Cogn Neurodyn, vol. 15, no. 2, pp.	cache/fuelectenerg-12594.pdf	txt/fuelectenerg-12594.txt