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A statistical analysis of Type-1 and Interval Type-2 Fuzzy Logic in dynamic parameter adaptation in the Bee Colony Optimization algorithm (BCO) is presented in this paper. The Bee Colony Optimization meta-heuristic belongs to the class of Nature-Inspired Algorithms. The objective of the work is based on the main reasons for the analysis of the approach with Interval Type-2 Fuzzy Logic to find the best parameters of the Beta and Alpha in BCO. We implemented the BCO specifically for tuning membership functions of the fuzzy controller for the benchmark problem, known as the temperature controller.

Statistical Analysis of Type-1 and Interval Type-2 Fuzzy Logic in dynamic parameter adaptation of the BCO