First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007) Meta-Regression: A Framework for Robust Reactive Optimization Cambridge, Massachussets July 09-July 11 ISBN: 0-7695-2906-2
DOI Bookmark: http://doi.ieeecomputersociety.org/10.1109/SASO.2007.37
Maintaining optimal performance as the conditions of a system change is a challenging problem. To solve this problem, we present meta-regression, a general methodology for alleviating traditional difficulties in nonlinear regression modelling. Meta-regression allows for reactive optimization, in which system components self-organize to changing conditions in a manner that is robust, or affected minimally by other sources of variability. Meta-regression extends profiling, providing a methodology for model-building when there is incomplete knowledge of the mechanisms and interactions of a nonlinear system.
Citation:
Daniel W. McClary, Violet R. Syrotiuk, Murat Kulahci, "Meta-Regression: A Framework for Robust Reactive Optimization," saso, pp.375-378, First International Conference on Self-Adaptive and Self-Organizing Systems (SASO 2007), 2007 Usage of this product signifies your acceptance of the Terms of Use. | |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
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