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We consider the problem of automatic construction of algorithms for recognition of abnormal behavior segments in phase trajectories of dynamic systems. The recognition algorithm is constructed using a set of examples of normal and abnormal behavior of the system. We use axiomatic approach to abnormal behavior recognition to construct abnormal behavior recognizers. In this paper we propose a modification of the genetic recognizer construction algorithm and a novel DTW-based recognition algorithm within this approach. The proposed modification reduces search space for the training algorithm and gives the recognition algorithm more information about phase trajectories. Results of experimental evaluation show that the proposed modification allows to reduce the number of recognition errors by an order of magnitude and to reduce the training time by a factor of 2 in comparison to the existing recognizer and recognizer construction algorithm.

A Modification of Training and Recognition Algorithms for Recognition of Abnormal Behavior of Dynamic Systems