@inproceedings{d8eb0863f3fd4725bf1fcf70fcdba9a7,
title = "Enhanced Conformal Predictors for Indoor Localisation Based on Fingerprinting Method",
abstract = "We proposed the first Conformal Prediction algorithm (CP) 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 showed 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.",
keywords = "indoor localisation, location fingerprinting, conformal prediction",
author = "Khuong Nguyen and Zhiyuan Luo",
year = "2013",
month = oct,
day = "2",
doi = "10.1007/978-3-642-41142-7_42",
language = "English",
isbn = "978-3-642-41141-0",
series = "IFIP Advances in Information and Communication Technology",
publisher = "Springer Berlin Heidelberg",
pages = "411--420",
booktitle = "9th IFIP International Conference on Artificial Intelligence Applications & Innovations (AIAI 2013)",
}