Performance improvement of multi-parameter measurement optical fiber sensors based on machine learning methods-Reference-Cited by-同舟云学术

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Performance improvement of multi-parameter measurement optical fiber sensors based on machine learning methods

Published:2023-07-31 Issue: Volume: Page:
ISSN:
Container-title:2023 21st International Conference on Optical Communications and Networks (ICOCN)
language:
Short-container-title:

Author:

Zhou Yi-Fan¹,Han Bo¹,Jin Po¹,Zhang Ya-Nan¹,Zhao Yong¹

Affiliation:

1. Northeastern University,College of Information Science and Engineering,Shenyang,China,110819

Funder

National Natural Science Foundation of China

Natural Science Foundation of Liaoning Province

Natural Science Foundation of Hebei Province

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/10235976/10235997/10236322.pdf?arnumber=10236322

Reference6 articles.

1. Machine Learning Implementation for Unambiguous Refractive Index Measurement Using a Self-Referenced Fiber Refractometer

2. Ultra-sensitive seawater temperature sensor using an FBG-cascaded microfiber MZI operating at dispersion turning point

3. Simultaneous measurement of temperature and magnetic field based on surface plasmon resonance and Sagnac interference in a D-shaped photonic crystal fiber

4. Machine Learning Assisted High-Sensitivity and Large-Dynamic-Range Curvature Sensor Based on No-Core Fiber and Hollow-Core Fiber

5. Refractive Index and Temperature Sensing System With High Sensitivity and Large Measurement Range Using an Optical Fiber

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