Makine Seçim Probleminin Bulanık VIKOR Yöntemiyle İncelenmesi

Ülkemizdeki Trafik Kazalarının Zamansal Değişimlerinin İncelenmesi

There is an imperative need to understand how, where and when traffic accidents occur in order to develop appropriate accident reduction strategies. An improved understanding of the location, time and reasons for traffic accidents makes a significant contribution to preventing them. Traffic accident occurrences have been extensively studied from different spatial and temporal points of view usi...

Polarization Measurement of High Dimensional Social Media Messages With Support Vector Machine Algorithm Using Mapreduce

Bu çalışmada önerilen yöntem kullanılarak, Eşle/İndirge (MapReduce) tekniği ile özellikle TFxIDF yöntemi gibi yüksek boyutlu veri setlerinin, veri madenciliğinde oldukça sık kullanılan makine öğrenme algoritmalarından olan Destek Vektör Makinesi (DVM) ile uygulanabilirliğini anlatılmaktadır. Literatürde, DVM sınıflandırma algoritması, makine öğrenmesi yöntemleri arasında genelleştirme özelliği ...

Yazılım Kalitesinin Karşılaştırılmasında TOPSIS VIKOR Yönteminin Uygulanması

Multi - sensor Target Recognition Based on VIKOR

Aiming at the target recognition problem of multi-sensor with multiple characteristic indexes, a new fusion method is proposed. The method firstly substitutes the distance of confidence for the ordinary attribute values, and the weights of attributes are derived by solving the optimal programming of maximizing the total square deviation of the confidence distance for all attributes. Then accord...

An extended VIKOR method using stochastic data and subjective judgments

Decision makers (DMs) face different levels of uncertainty throughout the decision making process. In particular, natural language is generally subjective or ambiguous when used to express perceptions and judgments. The aim of this paper is to extend the VIKOR method and develop a methodology for solving multi-criteria decision making (MCDM) problems with stochastic data. The weights of the sto...