Kernel Ridge Regression Based Modelling and Anomaly Detection for Temperature Control in Textile Dyeing Processes
Author:
Affiliation:
1. Eliar Electronics Corp.,İstanbul,Turkey
Publisher
IEEE
Link
http://xplorestaging.ieee.org/ielx7/10305866/10308427/10308428.pdf?arnumber=10308428
Reference11 articles.
1. Local Kernel Ridge Regression for Scalable, Interpolating, Continuous Regression;han;Transactions on Machine Learning Research,2022
2. A Realtime Temperature Anomaly Detection Method for IoT Data;wei;IoTBDS’20,0
3. Nonlinear forecasting with many predictors using kernel ridge regression
4. A Novel PI Auto-Tuning Method for Temperature Control in a Textile Dyeing Process;çom;2022 IEEE 17th International Conference on Control & Automation (ICCA),2022
5. Adsorption of organic dyes onto nanozeolites: A machine learning study
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1. Cloud-Based Machine Learning Methods for Parameter Prediction in Textile Manufacturing;Sensors;2024-02-18
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