Development and analysis of genetic algorithm for time series forecasting problem

Hulianytskyi L., Pavlenko A.

Int. J. "Information Models and Analyses". – 2015. – 4, N 1. – P. 13-29.


This paper presents developed genetic-based algorithm for time series forecasting problem and describes approaches to learning procedures design. Different techniques of population representation, recombination, formation of niches, calculation of fitness, conflict resolution methods are proposed. Results of computational experiments with real time series are analyzed.

Ключові слова: forecasting, genetic-based machine learning, rule-based forecasting, genetic algorithm, time series forecasting, evolutionary algorithms.

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