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Special Applications

  • Herbert RueferEmail author
Chapter
  • 446 Downloads

Abstract

A few mostly numerical examples show how to deal with challenging situations. If a system is affected by several different factors, such as components, subsystems, combinations, or options, an orthogonal array is applied to use minimal data as a generally rule. With the ongoing development aiming at higher system complexity, both, soft- and hardware fall within this category. It is not practicable to test all combinations. Assigning on-off situations as factors to an orthogonal array of adequate size is considerably easier and faster with unambiguous results. If a decision needs to be made it suffices to choose the result with the higher SNR index. For investigation and analysis, a system can be stressed to its limits if the model of prediction is confirmed. There is a chance to unravel basic technical, physical, or chemical relations to substitute empirical constants.

Keywords

Orthogonal arrayOrthogonal Array Correlation coefficientCorrelation Coefficient therapyTherapy Survival rateSurvival Rate Cumulative Class 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  1. 1.BurghausenGermany

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