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Time series modelling and forecasting using genetic algorithms

In this paper, Genetic Algorithms (GAs) are utilized in the investigation, design and development for modelling a given data time series. Genetic algorithms apply operations of reproduction, crossover and mutation to candidate solutions according to their relative fitness scores in the successive populations of candidates. The computer simulation results obtained demonstrate that GAs have the potential to become a powerful tool for time series modelling and forecasting.