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• W2181783669 abstract "In this paper, researchers have done scores of analyses on square cross-section brass structures in order to extract formulas with appropriate precisions, which can calculate the rate of absorption in these absorbers without performing numerous practical experiments. The results obtained from the experiments in this research are employed to represent a mathematical model based on Adaptive neuro-fuzzy inference systems (ANFIS) networks. Genetic algorithm (GA) and singular value decomposition (SVD) are deployed for the optimal design of both Gaussian membership functions of antecedents and the vector of linear coefficients of consequents in such networks, respectively. The aim of such modeling is to show how the value of absorbed energy varies with the variation of important parameters i.e., width of section, thickness and height of column. It is demonstrated that SVD can be effectively used to optimally find the vector of linear coefficients of conclusion parts in ANFIS models and their Gaussian membership functions in premise parts are established by GA." @default.
• W2181783669 created "2016-06-24" @default.
• W2181783669 creator A5077063508 @default.
• W2181783669 date "2012-01-01" @default.
• W2181783669 modified "2023-09-27" @default.
• W2181783669 title "Genetic Algorithm Optimized ANFIS Networks for Modeling and rediction of Energy Absorption rate of Brass Energy Absorbers" @default.
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