Fuzzy sets, uncertainty, and information
Fuzzy sets, uncertainty, and information
Time-series forecasting using GA-tuned radial basis functions
Information Sciences—Informatics and Computer Science: An International Journal - Special issue on evolutionary algorithms
Time-series prediction using adaptive neuro-fuzzy networks
International Journal of Systems Science
IEEE Transactions on Fuzzy Systems
Interval type-2 fuzzy logic systems: theory and design
IEEE Transactions on Fuzzy Systems
IEEE Transactions on Fuzzy Systems
Computing derivatives in interval type-2 fuzzy logic systems
IEEE Transactions on Fuzzy Systems
A fuzzy modeling method via Enhanced Objective Cluster Analysis for designing TSK model
Expert Systems with Applications: An International Journal
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This paper is focused on modelling of time series data which are corrupted by noise using type 2 fuzzy logic system (FLS). Type 2 FLS in which premise or consequent membership functions are type-2 fuzzy sets, can handle rule uncertainties. Type-2 FLS is very similar to a type-1 FLS, the major structural difference being that the defuzzifier block of a type-1 FLS is replaced by the output processing block in a type-2 FLS. That block consists of type-reduction followed by defuzzification. In the simulation results, Box-Jenkin's gas furnace time series will be demonstrated and we also compare the results of the type-2 fuzzy logic approach with the results of using only a traditional type-1 fuzzy logic approach.