Time-Series Forecasting using Optimisation Algorithms with Fuzzy Logic
Project summarySimulated annealing and genetic algorithms are being investigated for their ability to optimise fuzzy systems. A combination of fuzzy system models and simulated annealing is being used to predict time series with different levels of added noise. Simulated annealing has been used to optimise the parameters of the antecedent and the consequent parts of fuzzy system rules under singleton and non-singleton fuzzifications for both Mamdani and Takagi-Sugeno (TSK) fuzzy systems.
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