caa a22 4500 475833880 CHVBK 20180406123848.0 cr unu---uuuuu 170329e20000501xx s 000 0 eng 10.1007/s005210070034 doi (NATIONALLICENCE)springer-10.1007/s005210070034 A Fuzzy Modelling Approach Using Hierarchical Neural Networks [Elektronische Daten] [M.-Y. Chen, D.A. Linkens] A simple and effective fuzzy modelling approach is presented in this paper. A three-layer hierarchical clustering neural network is developed to build fuzzy rule-based models from numerical data. Differing from existing clustering-based methods, in this approach the structure identification of the fuzzy model is implemented on the basis of a class of sub-clusters created by a self-organising network instead of on raw data. By combined use of unsupervised and supervised learning, both structure identification and parameter optimisation of the fuzzy model can be carried out automatically. The simulation results show that the proposed method can provide good model structure for fuzzy modelling and has high computing efficiency.: Springer-Verlag London Limited, 2000 Keywords: Fuzzy clustering nationallicence Fuzzy modelling nationallicence Neural fuzzy systems nationallicence Non-linear system identification nationallicence Chen M.-Y Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK, GB aut Linkens D.A. Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK, GB aut https://doi.org/10.1007/s005210070034 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s005210070034 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Chen M.-Y Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK, GB aut NATIONALLICENCE 700 1- Linkens D.A. Department of Automatic Control and Systems Engineering, University of Sheffield, Sheffield, UK, GB aut Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer