Yazar "Yilmaz, Yusuf" seçeneğine göre listele

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    Modeling of the Effects of Cyclic Voltammetry (CV) Using Fuzzy Logic with Different Membership Functions for Proton Exchange Membrane Fuel Cell (PEM) with Polyvinyl Alcohol/Nano Silver (PVA/Ag)
    (TRANS TECH PUBLICATIONS LTD, 2017) Ersoyoglu, Ali Serhat; Ata, Sadik; Dincer, Kevser; Onal, Gurol; Yilmaz, Yusuf
    In this study, the effects of cyclic voltammetry (CV) has been modeled with Rule-based mamdani-type fuzzy (RBMTF), by using experimental data for proton exchange membrane fuel cell with PVA/AG. In the system developed, RBMTF apply input parameters are CV, scan rate and time, output parameters are current density and voltage. 12300 values for experimental study also obtained with RBMTF. Membership functions (MFs) are the building blocks of fuzzy set theory, i.e., fuzziness in a fuzzy set is determined by its MF. Accordingly, the shapes of MFs are important for a particular problem since they effect on a fuzzy inference system. They may have different shapes like triangular, trapezoidal, Gaussian, etc. When the results obtained from RBMTF and statistical analyses of experimental data have been compared, it has been determined that the two groups of data are coherent, and that there is not a significant difference between them. As a result, this study indicates that RBMTF with different membership functions can be safely used for CV.
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    Rule-based Mamdani-type fuzzy modeling of heating and cooling performances of counter-flow Ranque-Hilsch vortex tubes with different geometric construction for steel
    (PERGAMON-ELSEVIER SCIENCE LTD, 2013) Berber, Adnan; Dincer, Kevser; Yilmaz, Yusuf; Ozen, Dilek Nur
    In this study, heating and cooling performances of counter-flow Ranque-Hilsch vortex tubes (RHVT) were experimentally investigated and modeled with a RBMTF (Rule-Based Mamdani-Type Fuzzy) modeling technique. Input parameters (xi, L/D) and output parameters Delta T-h, Delta T-c were described by RBMTF if-then rules. 81 experimental data sets were used in the training step. Numerical parameters of input and output variables were fuzzificated as linguistic variables: Very Very Low (L1), Very Low (L2), Low (L3), Negative Medium (L4), Medium (L5), Positive Medium (L6), High (L7), Very High (L8) and Very Very High (L9) linguistic classes. R-2 for the Delta T-h was found to be 99.60% and R-2 for the Delta T-c was 99.80%. The actual values and RBMTF results indicated that RBMTF can be successfully used for the determination of heating and cooling performances of counter-flow RHVT with different geometric constructions for steel. (C) 2013 Elsevier Ltd. All rights reserved.