Accurate Mixed Weibull Distribution Fitting by Differential Evolution

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>

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

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Czech description

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Type

D - Article in proceedings

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)

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)

Publication year

2017

Confidentiality

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

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

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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