Enhanced Conformal Predictors for indoor localisation based on fingerprinting method

Khuong An Nguyen; Zhiyuan Luo

doi:10.1007/978-3-642-41142-7_42

Enhanced Conformal Predictors for indoor localisation based on fingerprinting method

Khuong An Nguyen, Zhiyuan Luo

Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN › peer-review

Abstract

We proposed the first Conformal Prediction (CP) algorithm for indoor localisation with a classification approach. The algorithm can provide a region of predicted locations, and a reliability measurement for each prediction. However, one of the shortcomings of the former approach was the individual treatment of each dimension. In reality, the training database usually contains multiple signal readings at each location, which can be used to improve the prediction accuracy.

In this paper, we enhance our former CP with the Kullback-Leibler divergence, and propose two new classification CPs. The empirical studies show that our new CPs performed slightly better than the previous CP when the resolution and density of the training database are high. However, the new CPs performs much better than the old CP when the resolution and density are low.

Original language	English
Title of host publication	Artificial Intelligence Applications and Innovations. AIAI 2013. IFIP Advances in Information and Communication Technology
Publisher	Springer
Pages	411-420
Volume	412
ISBN (Electronic)	9783642411427
ISBN (Print)	9783642411410
DOIs	https://doi.org/10.1007/978-3-642-41142-7_42
Publication status	Published - 2 Oct 2013

Publication series

Name	IFIP Advances in Information and Communication Technology
Publisher	Springer

Access to Document

10.1007/978-3-642-41142-7_42

Cite this

Nguyen, K. A., & Luo, Z. (2013). Enhanced Conformal Predictors for indoor localisation based on fingerprinting method. In Artificial Intelligence Applications and Innovations. AIAI 2013. IFIP Advances in Information and Communication Technology (Vol. 412, pp. 411-420). (IFIP Advances in Information and Communication Technology ). Springer. https://doi.org/10.1007/978-3-642-41142-7_42

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abstract = "We proposed the first Conformal Prediction (CP) algorithm for indoor localisation with a classification approach. The algorithm can provide a region of predicted locations, and a reliability measurement for each prediction. However, one of the shortcomings of the former approach was the individual treatment of each dimension. In reality, the training database usually contains multiple signal readings at each location, which can be used to improve the prediction accuracy.In this paper, we enhance our former CP with the Kullback-Leibler divergence, and propose two new classification CPs. The empirical studies show that our new CPs performed slightly better than the previous CP when the resolution and density of the training database are high. However, the new CPs performs much better than the old CP when the resolution and density are low.",

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Nguyen, KA & Luo, Z 2013, Enhanced Conformal Predictors for indoor localisation based on fingerprinting method. in Artificial Intelligence Applications and Innovations. AIAI 2013. IFIP Advances in Information and Communication Technology. vol. 412, IFIP Advances in Information and Communication Technology , Springer, pp. 411-420. https://doi.org/10.1007/978-3-642-41142-7_42

Enhanced Conformal Predictors for indoor localisation based on fingerprinting method. / Nguyen, Khuong An; Luo, Zhiyuan.
Artificial Intelligence Applications and Innovations. AIAI 2013. IFIP Advances in Information and Communication Technology. Vol. 412 Springer, 2013. p. 411-420 (IFIP Advances in Information and Communication Technology ).

Research output: Chapter in Book/Conference proceeding with ISSN or ISBN › Conference contribution with ISSN or ISBN › peer-review

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