Global Positioning System (GPS) is an advanced method for determining horizontal and vertical displacement. With the developing technology and data processing techniques, GPS can be used to determine the related/relative position and velocity of a point in millimeter accuracy. Deformation, which is the gradient of the displacement field, can be calculated by using GPS displacement vectors obtained from the measurements made in the interplate and plate boundaries and reveals important information about regional tectonics. Eastern Mediterranean, which has a very active tectonism, was chosen as study area within the scope of this study. In order to be able to examine the tectonic elements in the region, analysis was done in three stages. Deformation analysis was performed for three different areas by using GPS velocities of previous studies. The deformation analysis of the Eastern Mediterranean, which is a larger area, was firstly carried out, and then the area was reduced and the regional results of Cyprus and its surroundings were tried to be reached. Extension, shortening, dilatation and rotation maps of the study area were performed. Obtained deformation analysis results and the relationship between tectonics were interpreted together.
ABSTRACT:Many scholars have used microtremor applications to evaluate the vulnerability index. In order to reach fast and reliable results, microtremor measurement is preferred as it is a cost-effective method. In this paper, the vulnerability index will be reviewed by utilization of microtremor measurement results in Nicosia city. 100 measurement stations have been used to collect microtremor data and the data were analysed by using Nakamura's method. The value of vulnerability index (Kg) has been evaluated by using the fundamental frequency and amplification factor. The results obtained by the artificial neural network (ANN) will be compared with microtremor measurements. Vulnerability Index Assessment using Neural Networks (VIANN) is a backpropagation neural network, which uses the original input microtremor Horizontal Vertical Spectrum Ratio (HVSR) spectrum set. A 3-layer back propagation neural network which contains 4096 input, 28 hidden and 3 output neurons are used in this suggested system. The output neurons are classified according to acceleration sensitivity zone, velocity zones, or displacement zones.
ÖZBu çalışmada Çok-kanallı Yüzey Dalga Analizi yönteminden elde edilen Rayleigh dalgası dispersiyon eğrisinin ters çözümü için ardışık yaklaşım önerilmiştir. Ardışık yaklaşım için türev tabanlı Levenberg-Marquardt ve sezgisel bir yöntem olan Komşuluk Algoritması birlikte kullanılmıştır. Öncelikle düşük hızlı jeolojik birimler içeren sentetik modellerin kuramsal dispersiyon eğrileri hesaplanmıştır. Bir sonraki aşamada bu kuramsal dispersiyon eğrisine yüzde beş normal dağılıma uyan gürültü eklenmiştir. Levenberg-Marquardt Algoritması ile Komşuluk Algoritması ayrı ayrı kullanılarak ters çözüm işlemi gerçekleştirilmiş ve sonra ardışık ters çözüm uygulanarak elde edilen sonuç diğer iki sonuç ile karşılaştırılmıştır. Arazi çalışmasında ise İzmir ilinde Çok-kanallı Yüzey Dalga Analizi yöntemi ile toplanan veriler kullanılmıştır. Gerçekleştirilen ters çözüm işlemleri sonucunda elde edilen modeller mevcut sondaj verileri ve standart penetrasyon deneyi değerleri ile karşılaştırılmış ve sonuçların uyumlu olduğu görülmüştür. Önerilen ardışık yaklaşımın sentetik model çalışmasında doğru modele göreli olarak daha iyi yakınsadığı, gerçek arazi verisinde ise daha düşük hata ile modeli bulduğu görülmüştür.Anahtar Kelimeler: Çok-Kanallı Yüzey Dalga Analizi, dispersiyon eğrisi, ardışık yaklaşım, Komşuluk Algoritması. ABSTRACT In this study, a sequential approach is suggested to invert Rayleigh wave dispersion curves obtained from Multichannel Analysis of Surface Waves. The derivative based Levenberg-Marquardt algorithm and a stochastic method Neighbourhood Algorithm is used together for sequential approach. Firstly, the theoretical dispersion curve is created from forward solution of synthetic model that contains low-velocity layers and then five percent Gaussian type noise was added to the theoretical dispersion curve. The inversion of dispersion curve is carried out using Levenberg-Marquardt and Neighbourhood algorithms separately. Sequential approach is implemented for inversion on the same dispersion curves and the obtained results are compared. Root mean square error and relative error is calculated from the inversion results of the theoretical dispersion curves and the results
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