In order to overcome these drawbacks, two localization algorithms, namely weighted path loss (WPL) and extreme learning machine (ELM), are proposed in this ...
Two localization algorithms: Weighted Path Loss (WPL) and Extreme Learning Machine. (ELM) which can provide higher localization accuracy and ro- bustness than ...
An RFID Indoor Positioning System by Using Weighted Path Loss and Extreme Learning Machine. 2013. Han, Zou ... Main Content Metrics Author & Article Info.
Abstract: In recent years, applying RFID technology to develop an Indoor Positioning System (IPS) has become a hot research topic.
According to the algorithm, an indoor environment is divided into small zones firstly and an ELM model is developed for each zone during the offline phase.
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This paper is a preliminary work which seeks the possibilities of using Extreme Learning Machine (ELM) for location classification.
An RFID indoor positioning system by using weighted path loss and extreme learning machine · Computer Science, Engineering. 2013 IEEE 1st International ...
Furthermore, we also proposed three localization algorithms: Weighted Path Loss (WPL), Extreme Learning Machine (ELM) and integrated WPL-ELM. WPL is a ...
Jun 28, 2022 · H. Zou et al. An RFID indoor positioning system by using weighted path loss and extreme learning machine. (2013).
In this paper, we propose an RFID positioning algorithm based on the Glowworm Swarm Optimization (GSO) and semi-supervised online sequential extreme learning ...