Development issues in algorithms for system level self-diagnosis
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F44555601%3A13440%2F16%3A43887982" target="_blank" >RIV/44555601:13440/16:43887982 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.5604/20830157.1194261" target="_blank" >http://dx.doi.org/10.5604/20830157.1194261</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5604/20830157.1194261" target="_blank" >10.5604/20830157.1194261</a>
Alternative languages
Result language
angličtina
Original language name
Development issues in algorithms for system level self-diagnosis
Original language description
The paper deals with the problem of developing probabilistic algorithm for system level self-diagnosis. The main goal of the suggested algorithm is to minimize the mean time of its executing. The algorithm is based on the computing of the posterior probability of fault-free state of each system unit. Final decision about unit's state is made on the chosen decision rule. The execution of the probabilistic algorithm is elucidated with the help of simple example and then explained for the case of more complex systems.
Czech name
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Czech description
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Classification
Type
J<sub>ost</sub> - Miscellaneous article in a specialist periodical
CEP classification
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OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2016
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Informatyka Automatyka Pomiary w Gospodarce i Ochronie Srodowiska
ISSN
2083-0157
e-ISSN
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Volume of the periodical
2016
Issue of the periodical within the volume
1
Country of publishing house
PL - POLAND
Number of pages
3
Pages from-to
26-28
UT code for WoS article
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EID of the result in the Scopus database
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