Using Genetic Algorithms To Find Temporal Patterns Indicative Of Time Series Events
نویسنده
چکیده
A new framework for analyzing time series data called Time Series Data Mining (TSDM) is introduced. This framework adapts and innovates data mining concepts to analyzing time series data. In particular, it creates methods that reveal hidden temporal patterns that are characteristic and predictive of time series events. The TSDM framework, concepts, and methods, which use a genetic algorithm to search for optimal temporal patterns, are explained and the results are applied to real-world time series from the engineering and financial domains.
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