Data-Driven Design of Type-2 Fuzzy Logic System by Merging Type-1 Fuzzy Logic Systems
Type-2 fuzzy logic systems (T2 FLSs) have shown their superiorities in many real-world applications. With the exponential growth of data, it is a time consuming task to directly design a satisfactory T2 FLS through data-driven methods. This paper presents an ensembling approach based data-driven method to construct T2 FLS through merging type-1 fuzzy logic systems (T1 FLSs) which are generated using the popular ANFIS method. Firstly, T1FLSs are constructed using the ANFIS method based on the sub-data sets. Then, an ensembling approach is proposed to merge the constructed T1 FLSs in order to generate a T2 FLS. Finally, the constructed T2 FLS is applied to a wind speed prediction problem. Simulation and comparison results show that, compared with the well-known BPNN and ANFIS, the proposed method have similar performance but greatly reduced training time.
KeywordsData-driven method Fuzzy logic system ANFIS Wind speed prediction
This work is supported by National Natural Science Foundation of China (61473176, and 61573225), and the Natural Science Fund of Shandong Province for Outstanding Young Talents in Provincial Universities (ZR2015JL021).
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