A novel feature selection framework with Hybrid Feature-Scaled Extreme Learning Machine (HFS-ELM) for indoor occupancy estimation

• المؤلفون الرئيسيون: Mustafa Khalid Masood, Jiang, Chaoyang, Soh, Yeng Chai
• مؤلفون آخرون: School of Electrical and Electronic Engineering
• التنسيق: مقال
• اللغة: English
• منشور في: 2020
• الموضوعات: Engineering::Electrical and electronic engineering; ACMV; Occupancy Estimation
• الوصول للمادة أونلاين: https://hdl.handle.net/10356/142079

Indoor occupancy estimation can be an important parameter for automating Air Conditioning and Mechanical Ventilation (ACMV) operations in buildings. In this work, we propose a feature selection framework for constructing an occupancy estimator. The framework has two main components: a filter compone...