Fuzzy Modeling for Imprecise and Incomplete Data

Chapter
Part of the SpringerBriefs in Statistics book series (BRIEFSSTATIST)

Abstract

Fuzzy modeling is a methodology that works with partial truths: it can answer questions to which the answers are “yes” and “no” at different times or partly “yes” and “no” at the same time. It can be used to match any type of data, particularly incomplete and imprecise data, and it is able to improve precision of such data. It can be applied with any type of statistical distribution and it is, particularly, suitable for uncommon and unexpected non linear relationships.

Keywords

Membership Function Fuzzy Modeling Fuzzy Membership Linguistic Term Pharmacodynamic Modeling 
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

© The Author(s) 2012

Authors and Affiliations

  1. 1.SliedrechtThe Netherlands
  2. 2.LeidenThe Netherlands

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