期刊名称：Information Technology and Management Science
印刷版ISSN：2255-9086
电子版ISSN：2255-9094
出版年度：2015
卷号：18
期号：1
页码：70-77
DOI：10.1515/itms-2015-0011
语种：English
出版社：Walter de Gruyter GmbH
摘要：In the paper, a new hybrid system of computational intelligence is proposed. This system combines the advantages of neuro-fuzzy system of Takagi-Sugeno-Kang, type-2 fuzzy logic, wavelet neural networks and generalised additive models of Hastie-Tibshirani. The proposed system has universal approximation properties and learning capability based on the experimental data sets which pertain to the neural networks and neuro-fuzzy systems; interpretability and transparency of the obtained results due to the soft computing systems and, first of all, due to type-2 fuzzy systems; possibility of effective description of local signal and process features due to the application of systems based on wavelet transform; simplicity and speed of learning process due to generalised additive models. The proposed system can be used for solving a wide class of dynamic data mining tasks, which are connected with non-stationary, nonlinear stochastic and chaotic signals. Such a system is sufficiently simple in numerical implementation and is characterised by a high speed of learning and information processing.
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