AN EVOLUTIONARY APPROACH FOR IMPUTING MISSING DATA IN TIME SERIES
Autor: | Dusko Kalenatic, César Amilcar López Bello, Juan Carlos Figueroa Garcia |
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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 |
Externí odkaz: |
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. |
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ISSN: | 17936454 02181266 |
DOI: | 10.1142/s0218126610006050 |