Teri Hiltunen

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Self-organizing maps (SOM) have been successfully applied in many fields of research. In this paper, we demonstrate the use of a neural-network-based tool for a data analysis in fluidized bed energy plants. The software is based on selforganizing maps. Reference vectors of SOMs can be classified by K-means algorithm into clusters, which represented(More)
Energy producers are facing a challenging task in trying to monitor the energy conversion processes due to their complexity, nonlinear dynamics, and a large number of affecting factors. There are several methods available which can deal with multidimensionality and which could be used in industrial monitoring systems, but it seems that the methods used by(More)
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