Time Series Anomaly Detection via Rectangular Information Granulation for Sintering Process
Author:
Affiliation:
1. School of Automation, China University of Geosciences, Wuhan, China
2. Department of Electrical and Computer Engineering, University of Alberta, Edmonton, AB, Canada
Funder
China Postdoctoral Science Foundation
Hubei Provincial Natural Science Foundation of China
Higher Education Discipline Innovation Project
China University of Geosciences
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Link
http://xplorestaging.ieee.org/ielx7/91/10623556/10538420.pdf?arnumber=10538420
Reference22 articles.
1. Anomaly detection of the blast furnace smelting process using an improved multivariate statistical process control model
2. Application of Time Series Data Anomaly Detection Based on Deep Learning in Continuous Casting Process
3. An ensemble model based on weighted support vector regression and its application in annealing heating process
4. A Fuzzy Control Strategy of Burn-Through Point Based on the Feature Extraction of Time-Series Trend for Iron Ore Sintering Process
5. A 3-D Convolution-Based Burn-Through Point Multistep Prediction Model for Sintering Process
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