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- W2015402822 abstract "A method based on adaptive-network-based fuzzy infer- ence system (ANFIS) is presented for the quasi-static analysis of con- ductor-backed coplanar waveguides. The ANFIS is a class of adaptive networks which are functionally equivalent to fuzzy inference systems. Four optimization algorithms, hybrid learning, genetic, simulated an- nealing, and least-squares, are used to determine optimally the design parameters of the ANFIS. The results of ANFIS are compared with the results of experimental works, quasi-static and full-wave spectral do- main approaches, conformal mapping technique, and a commercial elec- tromagnetic simulator IE3D. The results of ANFIS models are in very good agreement with the results of other methods and experimental works. When the performances of ANFIS models are compared with each other, the best result is obtained from the ANFIS model trained by the hybrid learning algorithm. © 2008 Wiley Periodicals, Inc." @default.
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- W2015402822 date "2008-12-23" @default.
- W2015402822 modified "2023-10-17" @default.
- W2015402822 title "Analysis of conductor-backed coplanar waveguides using adaptive-network-based fuzzy inference system models" @default.
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- W2015402822 doi "https://doi.org/10.1002/mop.24059" @default.
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