- This paper presents the development of novel type-2 wavelet neural network system for time series prediction. The structure of type-2 Fuzzy Wavelet Neural Network (FAWN) is proposed and its learning algorithm is derived. The proposed network is constructed on the base of a set of fuzzy rules that includes type-2 fuzzy sets in the antecedent part and a wavelet function in the consequent part of the rules. For generating the structure of prediction model a fuzzy clustering algorithm is implemented to generate the rules automatically and the gradient learning algorithm is used for parameter identification. Type-2 FWNN is used for modelling and prediction of exchange rate time series. Effectiveness of the proposed system is evaluated with the results obtained from the simulation of type-2 FWNN based systems and with the comparative simulation results of previous related models.
NEAR EAST UNIVERSITY GRAND LIBRARY +90 (392) 223 64 64 Ext:5536. Near East Boulevard, Nicosia, TRNC This software is developed by NEU Library and it is based on Koha OSS
conforms to MARC21 library data transfer rules.