Accurate mixed weibuII distribution fitting by differential evolution
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216275%3A25410%2F17%3A39911936" target="_blank" >RIV/00216275:25410/17:39911936 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.1145/3071178.3071290" target="_blank" >http://dx.doi.org/10.1145/3071178.3071290</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.1145/3071178.3071290" target="_blank" >10.1145/3071178.3071290</a>
Alternative languages
Result language
angličtina
Original language name
Accurate mixed weibuII distribution fitting by differential evolution
Original language description
Mixed Weibull distribution is a probability distribution noted for its wide applicability in many diverse fields. The ability to accurately estimate mixed distribution parameters is essential for data-driven modeling, simulation, and analysis of the phenomena represented by mixed Weibull models. Nature-inspired metaheuristics for continuous parameter optimization have shown good potential for approximating parameters of complex statistical models. Differential evolution is a popular evolutionary real-parameter optimization method with good results in many areas. This work uses differential evolution to fit mixed Weibull distribution to data and analyzes the ability of different differential evolution variants to estimate mixture parameters.
Czech name
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Czech description
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Classification
Type
D - Article in proceedings
CEP classification
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OECD FORD branch
10103 - Statistics and probability
Result continuities
Project
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Continuities
I - Institucionalni podpora na dlouhodoby koncepcni rozvoj vyzkumne organizace
Others
Publication year
2017
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
GECCO 2017 : Proceedings of the 2017 Genetic and Evolutionary Computation Conference
ISBN
978-1-4503-4920-8
ISSN
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e-ISSN
neuvedeno
Number of pages
8
Pages from-to
1161-1168
Publisher name
ACM (Association for Computing Machinery)
Place of publication
New York
Event location
Berlín
Event date
Jul 15, 2017
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
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