Chemical Reaction Optimization for the Fuzzy Rule learning problem

摘要: In this paper, we utilize Chemical Reaction Optimization (CRO), a newly proposed metaheuristic for global optimization, to design Fuzzy Rule-Based Systems (FRBSs). CRO imitates the interactions of molecules in chemical reaction. The molecular structure corresponds solution, and potential energy is analogous objective function value. Molecules are driven toward lowest stable state, which optimum problem. realm modeling with fuzzy rule-based systems, automatic derivation rules from numerical data plays critical role. We propose use Cooperative Rules (COR) solve rule learning problem FRBS. formulate process FRBS form combinatorial optimization Our method COR-CRO evaluated by two benchmarks compared other algorithms. Simulation results demonstrate that highly competitive outperforms many existing methods.