EVALUATION OF PATTERN MATCHING ALGORITHMS FOR INDOOR LOCALIZATION VIA WLAN
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Keywords:
ANN
k-nearest neighbors
WLAN
MANET (mobile ad-hoc network)
indoor location system
Abstract
This study develops a software tool that can collect WLAN database from APs (Access Points) and use this database for estimating the location of user via pattern matching algorithms. There are 3 major pattern matching algorithms in this study: k-nearest Neighbors (k-NN), ηk-NN and Artificial Neural Network (ANN). Practical experiments use 2 test beds: test bed 1 has small area and not a noisy environment, test bed 2 has an area 14 times bigger than test bed1 and the environment is impacted by many noise sources for WLAN signal. The impact of factors like the number of samples, k, the number of perceptrons in the hidden layer of ANN and the size of testing environment are evaluated. Thereby, we can choose the best value for parameters to achieve the best accuracy.
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Published
Jul 31, 2014
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How to Cite
Nguyen Minh Hoang*;Phan Minh Nhat;Le Ty Khanh. “EVALUATION OF PATTERN MATCHING ALGORITHMS FOR INDOOR LOCALIZATION VIA WLAN”. The University of Danang - Journal of Science and Technology, vol. 7, no. 80, July 2014, pp. 5-9, https://jst-ud.vn/jst-ud/article/view/575.
