Title :
A genetic algorithm for construction of recognizers of anomalies in behaviour of dynamical systems
Author :
Kovalenko, Dmitry S. ; Kostenko, Valery A.
Author_Institution :
Fac. of Comput. Math. & Cybern., Lomonosov Moscow State Univ., Lomonosov, Russia
Abstract :
In this paper, the problem of automatic construction of recognizers of anomalies in behaviour of complicated dynamical systems is considered. Information about system behaviour is available in a form of multidimensional trajectories (time-series) obtained from sensors surrounding the system. A specific feature of the problem consists in the fact that, depending on the individual properties of the system and conditions of its operation, trajectories that contain anomalies may significantly differ from each other in amplitude and length. The genetic algorithm described here allows to construct recognizers of abnormal behaviour of complicated dynamical systems.
Keywords :
genetic algorithms; pattern recognition; anomalies recognizer; complicated dynamical system; genetic algorithm; sensor; Data mining; Irrigation; algebraic approach; dynamical system; genetic algorithm; machine learning; recognition algorithm; training set;
Conference_Titel :
Bio-Inspired Computing: Theories and Applications (BIC-TA), 2010 IEEE Fifth International Conference on
Conference_Location :
Changsha
Print_ISBN :
978-1-4244-6437-1
DOI :
10.1109/BICTA.2010.5645318
