<abstract xmlns="http://www.w3.org/1999/xhtml">

<p>The presented paper considers a comparison of the traditional methods for the state maximal probability determination to the proposed hybrid probabilistic and variational concept. It is shown the advantages of the described multi-optional hybrid-effectiveness functions uncertainty measure conditional optimization doctrine in the sense of avoiding the traditional ways analytical complicatedness concerning the maximal probability of the possible state determination. The results of the numerical example are presented.</p>
</abstract>

The presented paper considers a comparison of the traditional methods for the state maximal probability determination to the proposed hybrid probabilistic and variational concept. It is shown the advantages of the described multi-optional hybrid-effectiveness functions uncertainty measure conditional optimization doctrine in the sense of avoiding the traditional ways analytical complicatedness concerning the maximal probability of the possible state determination. The results of the numerical example are presented.

Multi-Optional Hybrid Functions Entropy Doctrine Advantages for a State Maximal Probability Determination

Transactions on Aerospace Research

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

The presented paper considers a comparison of the traditional methods for the state maximal probability determination to the proposed hybrid probabilistic and...

Multi-Optional Hybrid Functions Entropy Doctrine Advantages for a State Maximal Probability Determination

Online veröffentlicht: 18. Apr. 2020

Seitenbereich: 53 - 65

DOI: https://doi.org/10.2478/tar-2020-0004

Schlüsselwörter
entropy, dynamic state, risk, Markovian random process

© 2017 Copyright by Lukasiewicz Research Network – Institute of Aviation

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Multi-Optional Hybrid Functions Entropy Doctrine Advantages for a State Maximal Probability Determination

Online veröffentlicht: 18. Apr. 2020

Seitenbereich: 53 - 65

DOI: https://doi.org/10.2478/tar-2020-0004

Schlüsselwörterentropy, dynamic state, risk, Markovian random process

© 2017 Copyright by Lukasiewicz Research Network – Institute of Aviation

This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 3.0 License.

Schlüsselwörter
entropy, dynamic state, risk, Markovian random process