AN EVOLUTIONARY APPROACH FOR IMPUTING MISSING DATA IN TIME SERIES

Autor:	Dusko Kalenatic, César Amilcar López Bello, Juan Carlos Figueroa Garcia
Rok vydání:	2010
Předmět:	Fitness function Series (mathematics) Autocorrelation Evolutionary algorithm General Medicine Missing data computer.software_genre Error function Hardware and Architecture Genetic algorithm Data mining Electrical and Electronic Engineering Time series computer Mathematics
Zdroj:	Journal of Circuits, Systems and Computers. 19:107-121
ISSN:	1793-6454 0218-1266
DOI:	10.1142/s0218126610006050
Popis:	This paper presents a proposal based on an evolutionary algorithm for imputing missing observations in time series. A genetic algorithm based on the minimization of an error function derived from their autocorrelation function, mean, and variance is presented. All methodological aspects of the genetic structure are presented. An extended description of the design of the fitness function is provided. Four application examples are provided and solved by using the proposed method.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_________::c40d83320b8de380bc3f02c9fde61e4e https://doi.org/10.1142/s0218126610006050 Zobrazit plný text záznamu