The studied problem is prediction of time series based on preceding values of several time series (a multi-dimensional time series). Besides prediction itself, the task is finding precursors, i.e. determination of a set of the most significant input features in coordinates "initial time series - lag". A four-stage prediction algorithm based on neural network committee has been suggested, implemented and studied. The algorithm has been successfully tested on one model problem and on one real world problem. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Dolenko, S., Guzhva, A., Persiantsev, I., & Shugai, J. (2009). Multi-stage algorithm based on neural network committee for prediction and search for precursors in multi-dimensional time series. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5769 LNCS, pp. 295–304). https://doi.org/10.1007/978-3-642-04277-5_30
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