Yazar "Çağman, Naim" seçeneğine göre listele

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    A Generalisation of Fuzzy Soft Max-Min Decision-Making Method and Its Application to a Performance-Based Value Assignment in Image Denoising
    (TUBITAK, 2019) Enginoğlu, Serdar; Memiş, Samet; Çağman, Naim
    Latterly, the fuzzy soft max-min decision-making method denoted by FSMmDM and provided in [Çağman, N., Engino?lu, S., Fuzzy soft matrix theory and its application in decision making, Iranian Journal of Fuzzy Systems, 2012, 9(1), 109-119] has been configured via fuzzy parameterized fuzzy soft matrices (-matrices) by Enginoğlu and Memiş [A configuration of some soft decision-making algorithms via-matrices, Cumhuriyet Science Journal, 2018, 39(4), 871-881], faithfully to the original. Although this configured method denoted by CE12 and constructed by and-product/or-product (CE12a/CE12o) is useful in decision-making, the method should be made more attractive in terms of time and complexity in the event that a large amount of data is processed. In this paper, we propose two algorithms denoted by EMC19a and EMC19o and being new generalisations of FSMmDM. Moreover, we prove that EMC19a accept CE12a as a special case in the event that the first rows of the-matrices are binary. Afterwards, we compare the running times of these algorithms. The results show that EMC19a and EMC19o outperform CE12a and CE12o, respectively, in any number of data. We then apply EMC19o to a decision-making problem in image denoising. Finally, we discuss the need for further research. © 2019, TUBITAK. All rights reserved.
  • [ X ]
    Öğe
    Fuzzy parameterized fuzzy soft matrices and their application in decision-making
    (Isik University, 2020) Enginoğlu, Serdar; Çağman, Naim
    In this study, we define the concept of fuzzy parameterized fuzzy soft matrices (fpfs-matrices) and present some of their basic properties. By using fpfs-matrices, we then suggest a new algorithm, i.e. Prevalence Effect Method (PEM), and apply this method to a performance-based value assignment, so that we can order noise removal filters regarding performance. The results show that PEM has a potential for several areas, such as machine learning and image processing. Finally, we discuss fpfs-matrices and PEM for further research. © Isik University, Department of Mathematics, 2020.