Design of Safety FPGA Optimization Internet of things and Its Reliability Analysis

DOI

10.2991/icamcs-16.2016.12How to use a DOI?

Keywords

IOT, Welding Machine Monitoring System, Burst Detection, Sliding Window

Abstract

Aiming at demands based on abnormal condition detection and warning in welding machine monitoring system of IOT, put forward a burst detection algorithm for multi-population firefly, achieve optimization selection and configuration of sliding window size and improve the processing speed and detection performance of burst detection model through collaborative work of different species of fireflies. Simulation results show that burst detection algorithm based on multi-population firefly has less processing time and higher accuracy and recall rate than the traditional burst detection algorithm under the condition of same burst probability or maximum sliding window size.

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  - Lan Luan
PY  - 2016/06
DA  - 2016/06
TI  - Design of Safety FPGA Optimization Internet of things and Its Reliability Analysis
BT  - Proceedings of the 2016 5th International Conference on Advanced Materials and Computer Science
PB  - Atlantis Press
SP  - 52
EP  - 56
SN  - 2352-5401
UR  - https://doi.org/10.2991/icamcs-16.2016.12
DO  - 10.2991/icamcs-16.2016.12
ID  - Luan2016/06
ER  -