Scopus İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651

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Now showing 1 - 8 of 8
  • Editorial
    Introduction
    (Springer, 2008) Aydogan, N.
  • Article
    Citation - WoS: 51
    Citation - Scopus: 66
    Existence and Uniqueness of Solutions to Fractional Differential Equations in the Frame of Generalized Caputo Fractional Derivatives
    (Springer, 2018) Gambo, Y. Y.; Ameen, R.; Jarad, Fahd; Abdeljawad, T.
    The generalized Caputo fractional derivative is a name attributed to the Caputo version of the generalized fractional derivative introduced in Jarad et al. (J. Nonlinear Sci. Appl. 10:2607-2619, 2017). Depending on the value of. in the limiting case, the generality of the derivative is that it gives birth to two different fractional derivatives. However, the existence and uniqueness of solutions to fractional differential equations with generalized Caputo fractional derivatives have not been proven. In this paper, Cauchy problems for differential equations with the above derivative in the space of continuously differentiable functions are studied. Nonlinear Volterra type integral equations of the second kind corresponding to the Cauchy problem are presented. Using Banach fixed point theorem, the existence and uniqueness of solution to the considered Cauchy problem is proven based on the results obtained.
  • Conference Object
    Citation - Scopus: 1
    Induction for Radiology Patients
    (Springer, 2009) Yildirim, Pinar; Tolun, Mehmet R.
    This paper represents the implementation of an inductive learning algorithm for patients of Radiology Department in Hacettepe University hospitals to discover the relationship between patient demo-graphics information and time that patients spend during a specific radiology exam. ILA has been used for the implementation which generates rules and the results are evaluated by evaluation metrics. According to generated rules, some patients in different age groups or birthplaces may spend more time for the same radiology exam than the others.
  • Conference Object
    Citation - WoS: 1
    Citation - Scopus: 2
    Alternative Enhancement of Associativity Based Routing (Aeabr) for Mobile Networks
    (Springer, 2010) Preveze, B.; Şafak, A.
    This study proposes an alternative enhancement for the Enhanced Associativity Based Routing (EABR) method which is a derivation of ABR (Associativity Based Routing) by relative speed and relative distance estimation using the received power strength (RPS) of the nodes. In this study, it is shown that EABR outperforms some other well known protocols. The performance of EABR is improved in terms of number of route reconstructions (RRC) and connected status percentage (CSP). Message overhead and bandwidth utilization is also investigated. © 2010 ICST Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering.
  • Book Part
    A New Operator Approach for Solving Time-Fractional Nonlinear Burgess Equation
    (Springer, 2025) Arfaoui, H.; Kharrat, M.; Mecheri, H.; Baleanu, D.
    The introduction of fractional derivatives into the cancer treatment model continues to be improved with current cancer treatment. In this work, we define a new time-fractional nonlinear Burgess equation in order to model the brain tumor growth under treatment. The new mathematical model is in agreement with the clinical data proposed by Stupp et al. (2005). The numerical processing of this model is based on the splitting method which makes it possible to avoid and relax several numerical problems. The numerical results obtained are very satisfactory and excellent. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2025.
  • Book Part
    Strange Chaotic Attractors and Existence Results Via Nonlinear Fractional Order Systems and Fixed Points
    (Springer, 2024) Panda, S.K.; Vijayakumar, V.; Gopinadh, B.S.; Jarad, F.
    An analog of Meir-Keeler’s fixed point result in suprametric space is proved in this paper, and application to strange attractors in the context of the Atangana-Baleanu derivative is discussed. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
  • Article
    Citation - Scopus: 4
    Ion-Acoustic Solitons in Magnetized Plasma Under Weak Relativistic Effects on the Electrons
    (Springer, 2023) Madhukalya, B.; Das, R.; Hosseini, K.; Baleanu, D.; Salahshour, S.
    Investigating ion-acoustic disturbances in a magnetized plasma, consisting of relativistic electrons and non-thermal ions, entails a comprehensive study into the nonlinear wave structure. By condensing the fundamental set of fluid equations for the flow variables, a singular equation known as the Sagdeev potential equation is derived using the pseudopotential approach. In this investigation of the magnetized relativistic plasma, we have observed only dip (rarefactive) (N< 1) soliton under both subsonic (M< 1) and supersonic (M> 1) conditions. The occurrence of the soliton depends on the wave velocities in different propagation directions. The magnitude of amplitudes of the relativistic solitons is higher for higher Mach number (M> 1) irrespective of the wave’s propagation direction. Furthermore, the magnitude of amplitudes of the solitary wave is seen to increase near the direction of the magnetic field. © 2023, The Author(s), under exclusive licence to Springer Nature India Private Limited.
  • Book Part
    Citation - Scopus: 7
    Fractional Chebyshev Kernel Functions: Theory and Application
    (Springer, 2023) Hadian Rasanan, A.H.; Nedaei Janbesaraei, S.; Baleanu, D.
    Orthogonal functions have many useful properties and can be used for different purposes in machine learning. One of the main applications of the orthogonal functions is producing powerful kernel functions for the support vector machine algorithm. Maybe the simplest orthogonal function that can be used for producing kernel functions is the Chebyshev polynomials. In this chapter, after reviewing some essential properties of Chebyshev polynomials and fractional Chebyshev functions, various Chebyshev kernel functions are presented, and fractional Chebyshev kernel functions are introduced. Finally, the performance of the various Chebyshev kernel functions is illustrated on two sample datasets. © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd 2023.