ÖZTürkiye, deprem riski açısından dünyanın en önde gelen ülkelerindendir. Ülkemizin deprem haritası düşünüldüğünde geçmişte hemen hemen her bölgenin şiddetli depremlere maruz kaldığı gözlenmiştir. Türkiye, deprem tehlikesi açısından beş farklı bölgeye ayrılmaktadır. Bazı büyük şehirlerimizin birinci derece deprem bölgeleri üzerinde kuruldukları, nüfusumuzun yarıdan fazlasının buralarda yaşadığı bir gerçektir.Ekstrem değer teorisi ile istatistiksel analiz, doğadan elde edilen verilerin, kısa periyotlar göz önünde bulundurularak, uzun periyotlarda olan olayların olasılığını tahmin etmeyi amaçlar. Bu çalışmada, birinci derece deprem kuşağında bulunan Göller Bölgesi'ne ait deprem verilerinin ekstrem değer teorisi kullanılarak, hangi dağılıma uyduğu (Weibull, Gumbel, vs.) belirlenmiş ve belirlenen dağılıma ait parametre tahmini yapılmıştır. Bunlar yapılırken, yıllık maksimum şiddetteki depremler ele alınarak blok maksima yöntemi kullanılmıştır. Ayrıca, bu bölgede depremlerin gelecekte olma olasılıkları ve tekrarlanma periyotları tahmin edilmiştir.Anahtar Kelimler: Ekstrem değer teorisi, Blok maksima, Maksimum olabilirlik, Tekrarlanma seviyesi, Tekrarlanma periyodu. STATISTICAL ANALYSIS OF SIESMIC DATA BY EXTREME VALUE THEORY: LAKE REGION CASE ABSTRACTTurkey is one of the world's leading countries according to the earthquake risk. Considering the seismic map of Turkey, many strong earthquakes have been observed in almost every region. Turkey is divided into five different regions in terms of seismic hazard. Some of major cities have been established on a first-degree earthquake zone in Turkey and as a reality more than half of the population live in these cities.Extreme value analysis aims to make estimation of the probability of events for long periods using that of short periods obtained from nature. In this study, we fit a generalized extreme value distribution to the seismic data of Lake Region located in a first-degree earthquake zone and determined parameter estimates by block maxima method. In addition, we estimated return values and return periods for the data.
Wikipedia is a source that has been used at many universities around the world for students to gain some skills and be motivated positively. In higher education, some academicians have a positive view on the teaching usefulness of Wikipedia, and some of them are determined to use classical teaching. In this chapter, teaching use of Wikipedia in all faculty members of the Universitat Oberta de Catalunya are used as data. Then an entropy-based decision tree algorithm was developed. Wikipedia users and non-users are classified according to some aspects with this decision tree. Thus, it can be understood that whether Wikipedia has been used as a teaching tool by academicians or not. So, researchers can have information about the usefulness of Wikipedia in teaching and the intentions in use of it by academicians.
As a teaching tool, Wikipedia is used by an increasing number of professors from many universities around the world. Wikipedia is very influential in allowing students and teachers to learn together and having various skills for students. In this chapter, the influenced main factors of the teaching uses of Wikipedia in higher education are determined and also the relationship between these factors are tried to be explained with the technology acceptance model (TAM) through the structural equation model (SEM). With this aim, teaching use of Wikipedia in all faculty members of the Universitat Oberta de Catalunya are used as data and the data is analyzed by LISREL software package. After the analysis, it is found that sharing attitude and use behaviour factors have important role in the model and there is a direct strong impact of sharing attitude on use behavior.
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