Werner Groißböck, Edwin Lughofer,
"Online Adaptation of Correlation and Regression Models"
, 10-2002, Edwin Lughofer, Werner Groissböck, Online Adaptation of Correlation and Regression Models, Technical Report, Fuzzy Logic Laboratorium Linz-Hagenberg, October 2002.
Original Titel:
Online Adaptation of Correlation and Regression Models
Sprache des Titels:
Englisch
Original Kurzfassung:
Adaptive algorithms for data-based models are often
of fundamental importance in order to identify real-time
processes which possess a time-variant behaviour that would make a time-invariant model too inaccurate. Beyond that, an
insufficiency of amount, distribution and/or quality of actual recorded measurement data can occur, such that the model cannot meet the expectations at a particular time. In this case, the incorporation of new recorded data into previously generated models can improve the model's accuracy and reduce the bias or model error captured due to original noisy data. In this paper algorithms and strategies for adapting a special kind of
data-based models, namely so-called correlation and regression models, are demonstrated
Sprache der Kurzfassung:
Deutsch
Erscheinungsmonat:
10
Erscheinungsjahr:
2002
Notiz zum Zitat:
Edwin Lughofer, Werner Groissböck, Online Adaptation of Correlation and Regression Models, Technical Report, Fuzzy Logic Laboratorium Linz-Hagenberg, October 2002.