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Modelling and Optimization

  • Karl-HeinzSchmelovsky Schmelovsky
Conference paper
Part of the Advances in Simulation book series (ADVS.SIMULATION, volume 1)

Abstract

This paper is an attempt to get physical modeling and mathematical optimization somewhat closer together, using the concept of enlarged state space. Here, every influence, assumed to be neither’ exactly known nor totaly random, is described by state variables. This leads automatically to markoff processes in that state space. Furthermore state models can always be formulated so that observables depend only on actual state and — possible — on white time discrete noise.

Keywords

Statistic Strategy Hill Climb Statistical Disturbance Error Loss Function Hill Climb Technique 
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

© Akademie-Verlag Berlin 1988

Authors and Affiliations

  • Karl-HeinzSchmelovsky Schmelovsky
    • 1
  1. 1.Institut f. Kosmosforschung d. Adw d. DDRRudower ChausseeGermany

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