… (QoS) during the network selection decision. Thus, in this article, the authors investigate
graph theory and the AHP approach to deal with the network selection issue. The experimental …

… network selection in the context of selecting only one access technology. In this paper, we
investigate graph theory to model the network selection … path for network selection decision. …

… spectral graph theory methods to develop a systematic method for threshold selection. … a
transformation of the adjacency matrix of the network constructed at various threshold values. …

… that model and analyze brain network data, such as those provided by graph theory. This brief
review … insightful graph measures and techniques. Among these, the detection of network …

… and methods from the graph theory universe and we discuss ways in which they can be used
to reveal hidden properties and features of a network. This network profiling combined with …

… We report a novel application of graph theory that identifies the maximum set of unrelated
samples in any dataset given a user-defined threshold of relatedness as well as all networks of …

… In this article, we discuss the basic graph theory concepts and the various graph types, as
well … several network properties and we highlight some of the widely used network topological …

… As said, we are convinced that graph theory is a valuable tool for analyzing brain
networks but its use has its challenges asking for great care when interpreting results. …

… through a network graph. Furthermore, the network graph is analyzed by graph visualization
… Gephi 0.9 is used for network graph analysis and the graph theory metrics are investigated …

… presents the linkage between graph theory and spatial networks and gives a theoretical
description of our methodology. The testing of the method on the Helsinki street network and the …