Rayleigh model fitting to nonnegative discrete data

Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F67985556%3A_____%2F20%3A00531345" target="_blank" >RIV/67985556:_____/20:00531345 - isvavai.cz</a>
Alternative codes found
RIV/68407700:21260/20:00342031
Result on the web
<a href="http://dx.doi.org/10.1109/INES49302.2020.9147173" target="_blank" >http://dx.doi.org/10.1109/INES49302.2020.9147173</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1109/INES49302.2020.9147173" target="_blank" >10.1109/INES49302.2020.9147173</a>

Result language
angličtina
Original language name
Rayleigh model fitting to nonnegative discrete data
Original language description
The paper deals with modeling ordinal discrete random variables with a high number of nonnegative realizations. The prediction of the Rayleigh distribution learned on clusters of the explanatory variables is proposed. The proposed solution consists of the clustering and estimation phases based on the knowledge both of the target and explanatory variables, and the prediction phase using only the information from the explanatory variables. The main contributions of the approach are: (i) using the discretized knowledge of clusters of the explanatory variables and (ii) describing nonnegative discrete data by the multimodal Rayleigh distribution. Experiments with a data set from a tram network are provided.
Czech name
—
Czech description
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Project
<a href="/en/project/8A17006" target="_blank" >8A17006: (Ultra)Sound Interfaces and Low Energy iNtegrated SEnsors</a><br>
Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace

Publication year
2020
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Article name in the collection
Proceedings of 2020 IEEE 24th International Conference on Intelligent Engineering Systems (INES)
ISBN
978-1-7281-1059-2
ISSN
1543-9259
e-ISSN
—
Number of pages
6
Pages from-to
67-72
Publisher name
IEEE
Place of publication
Piscataway
Event location
Reykjavík
Event date
Jul 8, 2020
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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