Abstract
An approach to solving the problem of detecting and classifying anomalies and states of natural-technical systems and objects using swarm intelligence methods is considered. The main directions of development of the proposed approach include ant algorithms, bee swarm algorithms, and the particle swarm method. The structure of the swarm intelligence system of decision support based on collective preference rules is proposed. The application of the proposed approach makes it possible to optimize the processes of processing, analysis, integration of heterogeneous data, to increase the sensitivity, reliability and efficiency of decisions made.
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