Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection
Permanent URI for this collectionhttps://hdl.handle.net/11147/7148
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Article Citation - WoS: 3Citation - Scopus: 3Determining the Complexity of Multi-Component Conformal Systems: a Platoon-Based Approach(Elsevier Ltd., 2017) Koşun, Çağlar; Özdemir, SerhanMany systems in nature and engineering are composed of subsystems. These subsystems may be formed in a linear, planar or spatial array. A typical example of these formations is a chain of vehicles known as platoon formation in traffic flow. Platoon formation of vehicles is a linear or planar formation of vehicles where a certain and a constant headway, and sideway if applicable, is provided in between every and each one of them. It is argued in this paper that a well-automated platoon formation of vehicles is an extreme case of conformity. During this transformation from a many degrees of freedom formation to a solid object, Tsallis q value is computed to be ranging from one extreme case of q=3 to the other where q=1, when classified in terms of inverse temperatures of clearance fluctuations. At one extreme of q=3, one observes unbounded fluctuations in clearance fluctuations so that inverse temperature distributions approach a Dirac delta at the origin. At the other extreme of q=1, fluctuations in clearance tend to zero asymptotically, where a solid structure of agents (vehicles) emerges. The transition from q=3 to q=1 is investigated through synthetic and experimental clearance fluctuations between the cars. The results show that during the transition from q=3 to q=1, the platoon loses its many degrees of freedom (dof) of motion until a solid single object emerges. Authors assert that the Tsallis q value of a platoon of vehicles is limited to 3>q<1.Article Citation - WoS: 14Citation - Scopus: 15A Superstatistical Model of Vehicular Traffic Flow(Elsevier Ltd., 2016) Koşun, Çağlar; Özdemir, SerhanIn the analysis of vehicular traffic flow, a myriad of techniques have been implemented. In this study, superstatistics is used in modeling the traffic flow on a highway segment. Traffic variables such as vehicular speeds, volume, and headway were collected for three days. For the superstatistical approach, at least two distinct time scales must exist, so that a superposition of nonequilibrium systems assumption could hold. When the slow dynamics of the vehicle speeds exhibit a Gaussian distribution in between the fluctuations of the system at large, one speaks of a relaxation to a local equilibrium. These Gaussian distributions are found with corresponding standard deviations 1/β. This translates into a series of fluctuating beta values, hence the statistics of statistics, superstatistics. The traffic flow model has generated an inverse temperature parameter (beta) distribution as well as the speed distribution. This beta distribution has shown that the fluctuations in beta are distributed with respect to a chi-square distribution. It must be mentioned that two distinct Tsallis q values are specified: one is time-dependent and the other is independent. A ramification of these q values is that the highway segment and the traffic flow generate separate characteristics. This highway segment in question is not only nonadditive in nature, but a nonequilibrium driven system, with frequent relaxations to a Gaussian.Article Citation - WoS: 3Citation - Scopus: 2Prediction of Microdrill Breakage Using Rough Sets(Cambridge University Press, 2011) Sevil, Hakkı Erhan; Özdemir, SerhanThis study attempts to correlate the nonlinear invariants’ with the changing conditions of a drilling process through a series of condition monitoring experiments on small diameter (1 mm) drill bits. Run-to-failure tests are performed on these drill bits, and vibration data are consecutively gathered at equal time intervals. Nonlinear invariants, such as the Kolmogorov entropy and correlation dimension, and statistical parameters are calculated based on the corresponding conditions of the drill bits. By intervariations of these values between two successive measurements, a drop–rise table is created. Any variation that is within a certain threshold (+-20% of the measurements in this case) is assumed to be constant. Any fluctuation above or below is assumed to be either a rise or a drop. The reduct and conflict tables then help eliminate incongruous and redundant data by the use of rough sets (RSs). Inconsistent data, which by definition is the boundary re-gion, are classified through certainty and coverage factors. By handling inconsistencies and redundancies, 11 rules are ex-tracted from 39 experiments, representing the underlying rules. Then 22 new experiments are used to check the validity of the rule space. The RS decision frame performs best at predicting no failure cases. It is believed that RSs are superior in dealing with real-life data over fuzzy set logic in that actual measured data are never as consistent as here and may dominate the monitoring of the manufacturing processes as it becomes more widespread.