@inproceedings{72fa1c4b3b5f4cf6b5ae0b714501b51b,
title = "The application of SOM network to particle tracking velocimetry in a wind-blown sand flow",
abstract = "Wind-blown sand flow is the basic phenomena that have profound influences on the environment, and the experimental study on the velocity distribution of the sand particles is very important for the understanding of this phenomena. Among the various experimental techniques, particle tracking velocimetry (PTV for short) is one that attracts more and more attentions. In this paper, an algorithm based on the Self-Organizing Maps network is established for PTV in a wind-blown sand flow, and the processing results by the algorithm prove its ability to capture the characteristics of the concerning flow field.",
keywords = "Artificial neuron network, Particle tracking velocimetry, Recovery ratio, Self-organizing maps, Wind blown sand",
author = "Liqun Ji and Fusheng Yang and Min Guan",
note = "Publisher Copyright: {\textcopyright} 2015 IEEE.; 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015 ; Conference date: 24-04-2015 Through 26-04-2015",
year = "2015",
month = jun,
day = "9",
doi = "10.1109/ICISCE.2015.114",
language = "英语",
series = "Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "493--496",
editor = "Shaozi Li and Ying Dai and Yun Cheng",
booktitle = "Proceedings - 2015 2nd International Conference on Information Science and Control Engineering, ICISCE 2015",
}