Partition-based clustering with weighted feature is developed in the framework of shadowed sets. The objects in the core and boundary regions, generated by shadowed sets-based clustering, have different impact on the ...Partition-based clustering with weighted feature is developed in the framework of shadowed sets. The objects in the core and boundary regions, generated by shadowed sets-based clustering, have different impact on the prototype of each cluster. By integrating feature weights, a formula for weight calculation is introduced to the clustering algorithm. The selection of weight exponent is crucial for good result and the weights are updated iteratively with each partition of clusters. The convergence of the weighted algorithms is given, and the feasible cluster validity indices of data mining application are utilized. Experimental results on both synthetic and real-life numerical data with different feature weights demonstrate that the weighted algorithm is better than the other unweighted algorithms.展开更多
To avoid burst contention efficiently,on the basis of feedback-based source flow-rate control(SFC) strategy,a novel fuzzy-control-based assembly algorithm,called dual-fuzzy assembly threshold(DFAT),is proposed in an o...To avoid burst contention efficiently,on the basis of feedback-based source flow-rate control(SFC) strategy,a novel fuzzy-control-based assembly algorithm,called dual-fuzzy assembly threshold(DFAT),is proposed in an optical burst switching network.In our algorithm,according to the variations of burst assembly period and the interarrival of burst control packet,the traffic states of edge-switching nodes and core-switching nodes are first obtained.Then,the assembly threshold of bursts is set dynamically in order to operate the source traffic management from the information of traffic states.The performance of DFAT algorithm on burst loss probability is evaluated,and simulation results show that,compared with conventional assembly algorithms,the proposed scheme can constrain the birth of burst contention efficiently,when being a heavy load state of network.展开更多
基金Supported by the National Natural Science Foundation of China(61139002)~~
文摘Partition-based clustering with weighted feature is developed in the framework of shadowed sets. The objects in the core and boundary regions, generated by shadowed sets-based clustering, have different impact on the prototype of each cluster. By integrating feature weights, a formula for weight calculation is introduced to the clustering algorithm. The selection of weight exponent is crucial for good result and the weights are updated iteratively with each partition of clusters. The convergence of the weighted algorithms is given, and the feasible cluster validity indices of data mining application are utilized. Experimental results on both synthetic and real-life numerical data with different feature weights demonstrate that the weighted algorithm is better than the other unweighted algorithms.
基金Sponsored by the Science and Technology Project of Education Department of Heilongjiang Province (Grant No. 11521212)
文摘To avoid burst contention efficiently,on the basis of feedback-based source flow-rate control(SFC) strategy,a novel fuzzy-control-based assembly algorithm,called dual-fuzzy assembly threshold(DFAT),is proposed in an optical burst switching network.In our algorithm,according to the variations of burst assembly period and the interarrival of burst control packet,the traffic states of edge-switching nodes and core-switching nodes are first obtained.Then,the assembly threshold of bursts is set dynamically in order to operate the source traffic management from the information of traffic states.The performance of DFAT algorithm on burst loss probability is evaluated,and simulation results show that,compared with conventional assembly algorithms,the proposed scheme can constrain the birth of burst contention efficiently,when being a heavy load state of network.
