@inproceedings{b8fd3c1d0b4f4dbea8d3d2fc11e64071,
title = "Intelligent measurement in unmanned aerial cyber physical systems for traffic surveillance",
abstract = "An adaptive framework for building intelligent measurement systems has been proposed in the paper and tested on simulated traffic surveillance data. The use of the framework enables making intelligent decisions related to the presence of anomalies in the surveillance data with the help of statistical analysis, computational intelligent and machine learning. Computational intelligence can also be effectively utilised for identifying the main contributing features in detecting anomalous data points within the surveillance data. The experimental results have demonstrated that a reasonable performance is achieved in terms of inferential accuracy and data processing speed.",
keywords = "Artificial neural networks, Computational intelligence, Cyber physical system, Data anomalies, Intelligent measurement, Traffic surveillance",
author = "Andrei Petrovski and Prapa Rattadilok and Sergey Petrovskii",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2016.; 17th International Conference on Engineering Applications of Neural Networks, EANN 2016 ; Conference date: 02-09-2016 Through 05-09-2016",
year = "2016",
doi = "10.1007/978-3-319-44188-7_12",
language = "English",
isbn = "9783319441870",
series = "Communications in Computer and Information Science",
publisher = "Springer Verlag",
pages = "161--175",
editor = "Lazaros Iliadis and Chrisina Jayne",
booktitle = "Engineering Applications of Neural Networks - 17th International Conference, EANN 2016, Proceedings",
address = "Germany",
}