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Yayın Hybrid high dimensional model representation (HHDMR) on the partitioned data(Elsevier B.V., 2006-01-01) Tunga, Mehmet Alper; Demiralp, MetinA multivariate interpolation problem is generally constructed for appropriate determination of a multivariate function whose values are given at a finite number of nodes of a multivariate grid. One way to construct the solution of this problem is to partition the given multivariate data into low-variate data. High dimensional model representation (HDMR) and generalized high dimensional model representation (GHDMR) methods are used to make this partitioning. Using the components of the HDMR or the GHDMR expansions the multivariate data can be partitioned. When a cartesian product set in the space of the independent variables is given, the HDMR expansion is used. On the other band, if the nodes are the elements of a random discrete data the GHDMR expansion is used instead of HDMR. These two expansions work well for the multivariate data that have the additive nature. If the data have multiplicative nature then factorized high dimensional model representation (FHDMR) is used. But in most cases the nature of the given multivariate data and the sought multivariate function have neither additive nor multiplicative nature. They have a hybrid nature. So, a new method is developed to obtain better results and it is called hybrid high dimensional model representation (HHDMR). This new expansion includes both the HDMR (or GHDMR) and the FHDMR expansions through a hybridity parameter. In this work, the general structure of this hybrid expansion is given. It has tried to obtain the best value for the hybridity parameter. According to this value the analytical structure of the sought multivariate function can be determined via HHDMR.Yayın An automatic calibration procedure of driving behaviour parameters in the presence of high bus volume(Faculty of Transport and Traffic Engineering, 2019-11) Dadashzadeh, Nima; Ergün, Murat; Kesten, Ali Sercan; Zura, MarijanMost of the microscopic traffic simulation programs used today incorporate car-following and lane-change models to simulate driving behaviour across a given area. The main goal of this study has been to develop an automatic calibration process for the parameters of driving behaviour models using metaheuristic algorithms. Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and a combination of GA and PSO (i.e. hybrid GAPSO and hybrid PSOGA) were used during the optimization stage. In order to verify our proposed methodology, a suitable study area with high bus volume on-ramp from the 0-1 Highway in Istanbul has been modelled in VISSIM. Traffic data have been gathered through detectors. The calibration procedure has been coded using MATLAB and implemented via the VISSIM-MATLAB COM interface. Using the proposed methodology, the results of the calibrated model showed that hybrid GAPSO and hybrid PSOGA techniques outperformed the GA-only and PSO-only techniques during the calibration process. Thus, both are recommended for use in the calibration of microsimulation traffic models, rather than GA-only and PSO-only techniques.Yayın Multiresponse optimisation of powder metals via probabilistic loss functions(Inderscience Enterprises Ltd, 2013) Aksezer, Sezgin Çağlar; Benneyan, James C.Quadratic loss functions have been used extensively within the context of quality engineering and experimental design for process and product optimisation and robust design. In general, this approach determines optimal parameter settings based on minimising the sum of individual or mean loss of the associated response(s) of interest in a defined response surface. While the method is neat and handy, it totally neglects the effect of deviations on the desirable value of loss function. This paper utilises variance and probability distribution of loss functions for developing an in depth optimisation scheme that balances mean and variance of loss in a Pareto optimal manner. Since losses are usually defined in financial terms, this model then further improved to handle the user determined risk levels so that financial losses are being restricted within a certain region of interest. Application of the model is illustrated on a multiresponse optimisation problem from powder metallurgy industry.Yayın An immitance based tool for modelling passive one-port devices by means of darlington equivalents(Urban & Fischer Verlag, 2001) Yarman, Bekir Sıddık Binboğa; Aksen, Ahmet; Kılınç, AliAn immitance-based method is presented to model measured or computed data, obtained from a "passive one-port physical device" by means of its Darlington equivalent. In other words, the given data is modelled as a lossless two port terminated in a unit resistor. The basis of the new modelling tool rests on the numerical decomposition of the given immitance data into its Foster and minimum parts. Therefore, the proposed technique does not require any choice for the circuit topology to build the model. Rather, the optimum circuit topology that characterises the given data is the natural consequence of the modelling process proposed in this paper. A main algorithm is presented to construct the model from the given data. It is expected that the proposed modelling tool will find practical applications in the behaviour characterisation, simulation, and design of high speed/high frequency analog/digital mobile communication sub-systems manufactured on VLSI chips. An antenna-modelling example is included to systematically exhibit the implementation of the modelling technique.Yayın Saliency detection based on hybrid artificial bee colony and firefly optimization(Springer Science and Business Media Deutschland GmbH, 2022-11) Yelmenoğlu, Elif Deniz; Çelebi, Numan; Taşçı, TuğrulSaliency detection is one of the challenging problems still tackled by image processing and computer vision research communities. Although not very numerous, recent studies reveal that optimization-based methods provide relatively accurate and fast solutions for such problems. This paper presents a novel unsupervised hybrid optimization method that aims to propose reasonable solution to saliency detection problem by combining the familiar artificial bee colony and firefly algorithms. The proposed method, HABCFA, is based on creating hybrid-personality individuals behaving like both bees and fireflies. A superpixel-based method is used to obtain better background intensity values in the saliency detection process, providing a better precision in extracting the salient regions. HABCFA algorithm is capable of achieving an optimum saliency map without requiring any extra mask or training step. HABCFA has produced superior performance against its basis algorithms, artificial bee colony, and firefly on four known benchmark problems regarding convergence rate and iteration count. On the other hand, the experimental results on four commonly used datasets, including MSRA-1000, ECSSD, ICOSEG, and DUTOMRON, demonstrate that HABCFA is adequately robust and effective in terms of accuracy, precision, and speed in comparison with the eleven state-of-the-art methods.Yayın Investigation of residual stresses induced by milling of compacted graphite iron by x-ray diffraction technique(Springer, 2024-04) Kara, Mehmet Emre; Kuzu, Ali Taner; Bakkal, MustafaThis study investigates the relationship between residual stresses, cutting parameters, and machining performance in the milling process of compacted graphite iron (CGI). X-ray diffraction (XRD) analysis is employed to measure residual stresses on the cast and milled surfaces, while cutting force modeling is utilized to calculate the tangential force, power, and active work. The results demonstrate that tensile residual stresses are predominant on the milled surfaces, attributed to the both mechanical and thermal loads generated during milling. By analyzing various cutting conditions, it is observed that lower feeds contribute to reduced plastic deformation, resulting in lower residual stress levels. Additionally, higher cutting speeds lead to higher temperatures, but due to the shorter machining time, heat accumulation is limited, resulting in higher residual stresses, especially at low feeds. At high feeds, residual stresses decreased as the cutting speed increased. The interplay between cutting parameters and residual stresses highlights the need for optimizing cutting conditions to enhance fatigue strength in CGI components. These findings provide valuable insights for process optimization and quality control in the milling of CGI materials.
