Author:
Liu Shuqi,Zhou Xinzhi,Yu Junhui,Wang Yan,Xu Tao,Wang Hailin
Funder
Science and Technology on Reactor System Design Technology Laboratory Nuclear Power Institute of China
Reference21 articles.
1. Graph neural network-based anomaly detection in multivariate time series;Deng;Proc. AAAI Conf. Artif. Intell.,2021
2. Aging management of instrumentation & control sensors in nuclear power plants;Hashemian;Nucl. Eng. Des.,2010
3. Hines, J.W., Seibert, R., 2006. Technical Review of On-Line Monitoring Techniques for Performance Assessment. Volume 1. State-of-the-Art.
4. Hundman, K., Constantinou, V., Laporte, C., Colwell, I., Soderstrom, T., 2018. Detecting Spacecraft Anomalies Using LSTMs and Nonparametric Dynamic Thresholding, Proceedings of the 24th ACM SIGKDD International Conference on Knowledge Discovery & Data Mining. Association for Computing Machinery, London, United Kingdom, pp. 387–395. https://doi.org/10.1145/3219819.3219845.
5. An enhanced prediction model for the on-line monitoring of the sensors using the Gaussian process regression;Lee;J. Mech. Sci. Technol.,2019
Cited by
2 articles.
订阅此论文施引文献
订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献