Abstract
The growth in amount of data available today has encouraged the development of effective data analysis methods to support human decision-making. Neuro-fuzzy computation is a soft computing hybridisation combining the learning capabilities of the neural networks with the linguistic representation of data provided by the fuzzy models. In this paper, a framework to build temporally local neuro-fuzzy systems for the analysis of nonstationary process data using self-organizing operator maps is described. © Springer-Verlag Berlin Heidelberg 2003.
Cite
CITATION STYLE
Lehtimäki, P., Raivio, K., & Simula, O. (2003). Self-organizing operator maps in complex system analysis. Lecture Notes in Computer Science (Including Subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2714, 622–629. https://doi.org/10.1007/3-540-44989-2_74
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