КОНСТРУКТИВНО-ПРОДУКЦІЙНЕ МОДЕЛЮВАННЯ ДЕТЕРМІНОВАНИХ ЧАСОВИХ РЯДІВ З ФРАКТАЛЬНИМИ ВЛАСТИВОСТЯМИ

Abstract

This study represents the usage of the constructive-synthesizing modeling for deterministic fractal time series forecasting by finding the appropriate model. The constructive-synthesizing modeling was already successfully used for generation various time series using L-system and normal distribution. The main purpose of this research is the opposite process – find the model, which is related to the given values. The composite constructor has been developed and it consists of four interconnected constructors, which are performing actions from generating the time series to finding a corresponding model using genetic algorithm. The software solution has been developed to achieve the automatization of the testing process. There are four main stages of the experiments with different complexity of the time series models, starting with one-rule with four characters in the right part and ending with one-to-three rules with four-to-ten characters in the right part and complex axiom. The practical application of this solution is requiring further studying with using stochastic real-life time series.