Topology aggregation is necessary for scalable QoS routing mechanisms. Thekey issue is how to gain good performance while summarizing the topological information. In thispaper, we propose a new method to describe the ...Topology aggregation is necessary for scalable QoS routing mechanisms. Thekey issue is how to gain good performance while summarizing the topological information. In thispaper, we propose a new method to describe the logical link, which is simple and effective innetwork with additive and constrained concave parameters. We extend the method to network associatedwith multi-parameters. Furthermore, we propose a modified star aggregation algorithm. Simulationsare used to evaluate the performance. The results show that our algorithm is relatively good.展开更多
Among the available clustering algorithms in data mining, the CLOPE algorithm attracts much more attention with its high speed and good performance. However, the proper choice of some parameters in the CLOPE algorithm...Among the available clustering algorithms in data mining, the CLOPE algorithm attracts much more attention with its high speed and good performance. However, the proper choice of some parameters in the CLOPE algorithm directly affects the validity of the clustering results, which is still an open issue. For this purpose, this paper proposes a fuzzy CLOPE algorithm, and presents a method for the optimal parameter choice by defining a modified partition fuzzy degree as a clustering validity function. The experimental results with real data set illustrate the effectiveness of the proposed fuzzy CLOPE algorithm and optimal parameter choice method based on the modified partition fuzzy degree.展开更多
文摘Topology aggregation is necessary for scalable QoS routing mechanisms. Thekey issue is how to gain good performance while summarizing the topological information. In thispaper, we propose a new method to describe the logical link, which is simple and effective innetwork with additive and constrained concave parameters. We extend the method to network associatedwith multi-parameters. Furthermore, we propose a modified star aggregation algorithm. Simulationsare used to evaluate the performance. The results show that our algorithm is relatively good.
基金Supported by the National Natural Science Foundation of China (No.60202004).
文摘Among the available clustering algorithms in data mining, the CLOPE algorithm attracts much more attention with its high speed and good performance. However, the proper choice of some parameters in the CLOPE algorithm directly affects the validity of the clustering results, which is still an open issue. For this purpose, this paper proposes a fuzzy CLOPE algorithm, and presents a method for the optimal parameter choice by defining a modified partition fuzzy degree as a clustering validity function. The experimental results with real data set illustrate the effectiveness of the proposed fuzzy CLOPE algorithm and optimal parameter choice method based on the modified partition fuzzy degree.
