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Accurate Mixed Weibull 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%2F61989100%3A27240%2F17%3A10238704" target="_blank" >RIV/61989100:27240/17:10238704 - isvavai.cz</a>

  • Result on the web

    <a href="https://dl.acm.org/citation.cfm?doid=3071178.3071290" target="_blank" >https://dl.acm.org/citation.cfm?doid=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 Weibull Distribution Fitting by Differential Evolution

  • Original language description

    Mixed Weibull distribution is a probability distribution noted for its wide applicability in many diverse fields. Thee 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

  • Czech description

Classification

  • Type

    D - Article in proceedings

  • CEP classification

  • OECD FORD branch

    10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Result continuities

  • Project

    <a href="/en/project/GJ16-25694Y" target="_blank" >GJ16-25694Y: Multi-paradigm data mining algorithms based on information retrieval, fuzzy, and bio-inspired methods</a><br>

  • Continuities

    P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

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

  • e-ISSN

    neuvedeno

  • Number of pages

    8

  • Pages from-to

    1161-1168

  • Publisher name

    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