JOURNAL ARTICLE

An accurate ensemble-based wireless localization strategy for wireless sensor networks

Abstract

In wireless systems, localization is still an important challenge to ensure innovative based services solutions. In this paper, a novel localization algorithm which intends to improve robustness and accuracy of previous work based on regression tree is proposed. The suggested approach is a learning based ensemble technique which combines several regression trees. Anchor selection procedure is associated to the proposed algorithm to ensure better performance. We take into consideration two performance keys : the localization error and the computation complexity. Experimental results show that the ensemble method is simple and accurate compared to localization algorithms currently available in the literature.

Keywords:
Robustness (evolution) Computer science Wireless sensor network Ensemble learning Wireless Computation Artificial intelligence Decision tree Machine learning Simple (philosophy) Wireless network Tree (set theory) Data mining Algorithm Computer network Mathematics

Metrics

3
Cited By
0.48
FWCI (Field Weighted Citation Impact)
15
Refs
0.73
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Indoor and Outdoor Localization Technologies
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Underwater Vehicles and Communication Systems
Physical Sciences →  Engineering →  Ocean Engineering
Energy Efficient Wireless Sensor Networks
Physical Sciences →  Computer Science →  Computer Networks and Communications
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