Abstract
Many practical tasks require discovering interconnections between the behavior of a complex object and events initiated by this behavior or correlating with it. In such cases it is supposed that emergence of an event is preceded by some phenomenon – a combination of values of the features describing the object, in a known range of time delays. Recently the authors suggested a neural network based method of analysis of such objects. In this paper, the results of experiments on real-world data are presented. The method aims at revealing morphological and dynamical features causing the event or preceding its emergence.
An erratum to this chapter can be found at http://dx.doi.org/10.1007/11550907_163 .
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Dolenko, S.A., Orlov, Y.V., Persiantsev, I.G., Shugai, J.S. (2005). Neural Network Algorithm for Events Forecasting and Its Application to Space Physics Data. In: Duch, W., Kacprzyk, J., Oja, E., Zadrożny, S. (eds) Artificial Neural Networks: Formal Models and Their Applications – ICANN 2005. ICANN 2005. Lecture Notes in Computer Science, vol 3697. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11550907_83
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DOI: https://doi.org/10.1007/11550907_83
Publisher Name: Springer, Berlin, Heidelberg
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