Sökning: "Clustering Algorithm"
Visar resultat 11 - 15 av 97 avhandlingar innehållade orden Clustering Algorithm.
11. Graph Partitioning and Planted Partitions
Sammanfattning : Graph partitioning is the problem of splitting a graph into two or morepartitions of fixed sizes while minimizing the number of edges that are “cut”.This is an important problem with a wide range of applications in fields suchas VLSI design, parallel processing, bioinformatics, data mining etc. LÄS MER
12. Adaptive Real-time Anomaly Detection for Safeguarding Critical Networks
Sammanfattning : Critical networks require defence in depth incorporating many different security technologies including intrusion detection. One important intrusion detection approach is called anomaly detection where normal (good) behaviour of users of the protected system is modelled, often using machine learning or data mining techniques. LÄS MER
13. Approximations of Bayes Classifiers for Statistical Learning of Clusters
Sammanfattning : It is rarely possible to use an optimal classifier. Often the classifier used for a specific problem is an approximation of the optimal classifier. Methods are presented for evaluating the performance of an approximation in the model class of Bayesian Networks. LÄS MER
14. Modeling and constructing unstructured overlay networks: Algorithms, techniques and the Smart Grid case
Sammanfattning : Throughout its lifetime, the Internet was always associated with overlay networks; from the WorldWideWeb and peer-to-peer networks to blogs and social networking solutions, overlays built on the Internet infrastructure gave it additional value and made it more engaging to everyday users. Today, rising overlay networks such as the Smart Grid as well as a multitude of sensor, mobile andwireless networks herald a new era of unprecedented connectivity and networking. LÄS MER
15. Structural Models of Network Contacts Between Actors Governed by Activity and Attraction
Sammanfattning : This thesis consists of five papers on the subject of statistical modeling of stochastic networks. The NG-model proposed in Paper I combines a block structure with parameters that capture the identities of vertices and thus the new approach stresses the concept of ego-nets, which describes the structure around identified vertices. LÄS MER