The Signal Detection Model of AM-EAS Based on Optimized SVM with Improved AFSA

DOI

10.2991/meici-16.2016.73How to use a DOI?

Keywords

Artificial Fish Swarm Algorithm;SVM;AM label;Detection rate;Real-time

Abstract

In order to improve the detection rate of AM-EAS system, The paper puts forward an new signal detection model (IAFSA-SVM) combined with the Improved Artificial Fish Swarm Algorithm (IAFSA) and Support Vector Machine (SVM) .the paper analyzed the advantage and defect of AFSA, and proposed the improved scheme, The simulation results show that IAFSA than AFSA, GA and PSO has a better ability of parameters optimization about SVM,The model based on the optimized SVM compared with the traditional AM label detection algorithm has markedly improved in detection rate and false positives, and satisfies the requirement of real-time detection in engineering application.

Copyright

© 2016, 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  - Yanan Geng
PY  - 2016/09
DA  - 2016/09
TI  - The Signal Detection Model of AM-EAS Based on Optimized SVM with Improved AFSA
BT  - Proceedings of the 2016 6th International Conference on Management, Education, Information and Control (MEICI 2016)
PB  - Atlantis Press
SP  - 352
EP  - 356
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-16.2016.73
DO  - 10.2991/meici-16.2016.73
ID  - Geng2016/09
ER  -