Evolutionary Optimization for the Belief-Rule-Based System: Method and Applications
نویسندگان
چکیده
Evolutionary optimization (EO) has been proven to be highly effective computation means in solving asymmetry problems engineering practices. In this study, a novel evolutionary approach for the belief rule base (BRB) system is proposed, namely EO-BRB, by constructing an model and employing Differential (DE) algorithm as its engine due ability locate optimal solution with nonlinear complexity. EO-BRB approach, most representative referenced values of attributes which are pre-determined traditional learning approaches optimized. model, mean squared error (MSE) between actual observed data taken objective, while initial weights all rules, beliefs scales conclusion part, restraints. Compared BRB system, (1) does not require transforming numerical into linguistic terms; (2) identifying any solution; (3) mathematical deduction and/or case-specific information verifies it general approach; (4) can help downsize producing superior performances. Thus, proposed make best use modeling superiority EO algorithms. Three practical cases studied validate efficiency approach.
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ژورنال
عنوان ژورنال: Symmetry
سال: 2022
ISSN: ['0865-4824', '2226-1877']
DOI: https://doi.org/10.3390/sym14081622