Enhancing Wearable-Based Human Activity Recognition with Binary Nature-Inspired Optimization Algorithms for Feature Selection

• 主要な著者: Norfadzlan, Yusup, Izzatul Nabila, Sarbini, Dayang Nurfatimah, Awang Iskandar, Azlan, Mohd Zain, Didik Dwi, Prasetya
• フォーマット: 論文
• 言語: English
• 出版事項: Semarak Ilmu Publishing 2026
• 主題: QA Mathematics; QA75 Electronic computers. Computer science
• オンライン･アクセス: http://ir.unimas.my/id/eprint/47674/1/ARASETV56_N1_PP1_12.pdf; http://ir.unimas.my/id/eprint/47674/; https://semarakilmu.com.my/journals/index.php/applied_sciences_eng_tech/article/view/6092; https://doi.org/10.37934/araset.56.1.112

This research paper explores the performance of binary nature-inspired optimization algorithms as feature selection to enhance the identification of human activities using wearable technology. Utilization of nature-inspired algorithms for feature selection, as documented in scholarly literature, pr...