Decay-parameter Diagnosis in Industrial Domains by Robustness through Isotonic Regression
Autor: | Patrick Praher, Salma Mahmoud, Jorge Martinez-Gil, Bernhard Freudenthaler, Florian Sobieczky |
---|---|
Rok vydání: | 2021 |
Předmět: |
Heteroscedasticity
Scale (ratio) Computer science Industrial production Mode (statistics) 020206 networking & telecommunications 02 engineering and technology Noise Identification (information) Robustness (computer science) 0202 electrical engineering electronic engineering information engineering General Earth and Planetary Sciences Isotonic regression 020201 artificial intelligence & image processing Biological system General Environmental Science |
Zdroj: | Procedia Computer Science. 180:466-475 |
ISSN: | 1877-0509 |
Popis: | In various industrial production environments a burn-in phase of a specific settling-length precedes a stable (i.e. steady-state, stationary) process mode. The identification of the corresponding physical parameters may be difficult to perform in the presence of strong noise. We propose a method using isotonic regression which circumvents the negative effects of heteroscedasticity related to naive estimation procedures adding robustness against different occurrences of scale on which the run-in effect is observed. |
Databáze: | OpenAIRE |
Externí odkaz: |