Prediction Using Relational Models

  • José Valente de Oliveira
Part of the International Series in Intelligent Technologies book series (ISIT, volume 7)


Prediction is the problem of extrapolating a given signal sequence (or time series) into the future. The many theoretical assumptions required for the formulation of well-posed problems using relational models are stated. Specific issues of the identification and modelling of dynamic systems are studied. These include model feedback topologies, and the concerns with the maintenance of the set-theoretical (or logical) nature of fuzzy models during parameter estimation. Examples are included. A typical prediction application crystalized in the form of a predictive control algorithm is presented and applied to the control of a physical system.


Membership Function Fuzzy System Output Interface Defuzzification Method Parameter Estimation Algorithm 
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.


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Copyright information

© Kluwer Academic Publishers 1996

Authors and Affiliations

  • José Valente de Oliveira
    • 1
  1. 1.Research Group on Control of Dynamic SystemsINESCLisboaPortugal

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