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Hybrid algorithm of learning for optimization of solutions for monitoring

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ARTICLE ANNOTATION

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The application of intelligent monitoring systems and support decision-making weakly formalized basic functional tasks are classification, clustering, pattern recognition, forecasting, assessment of conditions, identification of patterns between the parameters of different types of optimization and decision making. Distinctive features of these types of tasks are the following: large dimensionality multicriteriality, the uncertainties in the initial information and the situation, the dynamic changes in the environment settings, predictability which often is difficult or impossible. These features cause the use to solve these problems, along with traditional methods and tools of operations research and data mining (IBP), intelligent technologies based on informal empirical knowledge of experts and logical reasoning, as well as natural and biological mechanisms of learning, evolution, adaptation and optimization.

AUTHORS

N.Niyozmatova

Toshkent axborot texnologiyalari universiteti

Tags

# многокритериальность# гибридный алгоритм# задача оптимизации# интеллектуальная система# hybrid algorithm# optimization problem# an intelligent system# multicriteriality# гибрид алгоритм# оптимизация масаласи# интеллектуал тизим# кўп мезонлилик

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