Research on Machine Learning Algorithm-Based Approach for Detecting Abnormal Data from Environmental Sensors in Different Dimensions-Reference-Cited by-同舟云学术

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Research on Machine Learning Algorithm-Based Approach for Detecting Abnormal Data from Environmental Sensors in Different Dimensions

Published:2023-07-07 Issue: Volume:48 Page:26-33
ISSN:
Container-title:Proceedings of the 2023 International Joint Conference on Robotics and Artificial Intelligence
language:
Short-container-title:

Author:

Yue Wenqiang¹^ORCID,Chen Li-an²^ORCID,Huang Haiyan³^ORCID

Affiliation:

1. School of Electrical Engineering and Automation, Xiamen University of Technology, China

2. School of Electrical Engineering and Automation, Xiamen Key Laboratory of Frontier Electric Power Equipment and Intelligent Control, Xiamen University of Technology, China

3. Xiamen Minghan Electric Co.,Ltd., China

Funder

Natural Science Foundation of Fujian Province of Grant

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3632971.3632990

Reference16 articles.

1. Hao Z J Xu H W Dang X C 2020. Method for Patching Three-Dimensional Surface Coverage Loopholes of Hybrid Nodes in Wireless Sensor Nerworkst. Journal of Sensors no.1. https://doi.org/10.1155/2020/6492457

2. Xiong Juxia, Wu Jinzhao. 2020. Dynamic tracking simulation of abnormal nodes in high-dimensional data stream, Computer simulation, vol.37, no.10, 445-449.

3. Unsupervised anomaly detection method for high-dimensional big data analysis;Chengming Zou;Computer Science,2021

4. Unsupervised deep anomaly detection model based on sample association perception;Liang Xi;Journal of Computer Science,2021

5. An Ensemble-Based Approach to Anomaly Detection in Marine Engine Sensor Streams for Efficient Condition Monitoring and Analysis

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