Asynchronous Data Recognition Research Based on Interval Association Degree

DOI

10.2991/ncce-18.2018.13How to use a DOI?

Keywords

Target recognition; Interval association degree; Sequence data and Interval number.

Abstract

Aiming at the problem that the sequence data can’t be fused with the interval data in the database directly, the sequence-interval asynchronous data recognition algorithm based on interval association degree was proposed. First of all, reduce the dimension of the sequence data, use the maximum and minimum of the sequence data as the interval boundary, complete the isomorphism transformation of the asynchronous data and then solve the interval similarity degree. Finally, use a recognition algorithm based on adaptive recognition criterion to deal with the indistinguishability of the recognition algorithm of the maximum association degree when association degree is fuzzy. Simulation experiments show that the proposed algorithm can recognize sequence-interval asynchronous data effectively and also discuss the recognition effect of the adaptive recognition algorithm and the maximum association degree recognition algorithm.

Copyright

© 2018, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Jing Zhao
AU  - Xin Guan
AU  - Guidong Sun
AU  - Haiqiao Liu
PY  - 2018/05
DA  - 2018/05
TI  - Asynchronous Data Recognition Research Based on Interval Association Degree
BT  - Proceedings of the 2018 International Conference on Network, Communication, Computer Engineering (NCCE 2018)
PB  - Atlantis Press
SP  - 75
EP  - 83
SN  - 1951-6851
UR  - https://doi.org/10.2991/ncce-18.2018.13
DO  - 10.2991/ncce-18.2018.13
ID  - Zhao2018/05
ER  -