Desarrollos Conceptuales en Programación Genética para la predicción de Series de Tiempo (Conceptual Developments in Genetic Programming for Time Series Forecasting)

Carlos A. Martinez (amartin77@gmail.com)1, Juan David Velasquez (jdvelasq@unal.edu.co)1


1Universidad Nacional de Colombia

This paper appears in: Revista IEEE América Latina

Publication Date: Aug. 2015
Volume: 13,   Issue: 8 
ISSN: 1548-0992


Abstract:
Objective: The aim of this paper is to analyze the main research areas in Genetic Programming (GP). Method: We used the systematic literature review method employing an automatic search with manual refining of papers published on GP between 1992 to 2012. Results: Just 63 studies meet all the requirements of the inclusion criteria. Conclusion: Although studies relating to the application of genetic programming in the forecast of time series were frequently presented, we find that the studies proposing changes in the original algorithm of GP with a theoretical support and a systematic procedure for the construction of model were scarce in the time 1992-2012.

Index Terms:
Nonlinear models, Genetic programming, Forecasting, Neural Networks, Genetic Algorithms, Time series   


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