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:
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
Popis
Abstrakt: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.
ISSN:17936454
02181266
DOI:10.1142/s0218126610006050