Sea Ice Type and Thickness Identification Based on Vibration Sensor Networks and Machine Learning-Reference-Cited by-同舟云学术

Sea Ice Type and Thickness Identification Based on Vibration Sensor Networks and Machine Learning

Published:2023 Issue: Volume:72 Page:1-11
ISSN:0018-9456
Container-title:IEEE Transactions on Instrumentation and Measurement
language:
Short-container-title:IEEE Trans. Instrum. Meas.

Author:

Zhao Yuliang¹^ORCID,Sun Zhiwei¹^ORCID,Li Weishi¹^ORCID,Tian Kaixuan¹^ORCID,Zhan Zhikun²^ORCID,Shan Peng¹^ORCID,Li Lianjiang¹^ORCID

Affiliation:

1. Hebei Key Laboratory of Micro-Nano Precision Optical Sensing and Measurement Technology and the School of Control Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China

2. College of Computer Science and Engineering, Northeastern University at Qinhuangdao, Qinhuangdao, China

Funder

National Natural Science Foundation of China

Hebei Natural Science Foundation

Fundamental Research Funds for the Central Universities

Administration of Central Funds Guiding the Local Science and Technology Development

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Instrumentation

Link

http://xplorestaging.ieee.org/ielx7/19/10012124/10113291.pdf?arnumber=10113291

Reference37 articles.

1. Ice Condition Assessment Using Onboard Accelerometers and Statistical Change Detection

2. The coefficient of determination R-squared is more informative than SMAPE, MAE, MAPE, MSE and RMSE in regression analysis evaluation

3. IMU Sensor-based Vibration Measuring of Ship Sailing

4. Machine Learning Algorithms for the Forecasting of Wastewater Quality Indicators

5. A remote monitoring system of temperature and humidity based on OneNet cloud service platform

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