In this paper, a dynamic evidential clustering algorithm (DEC) is introduced to address the computational burden of existing methods. To derive such solution, an FCM-like objective function first employed and minimized obtain support levels real singletons (specific) clusters which query objects belong, then initially adaptively assigned outlier, precise or imprecise one via new rule-based on c...

in this research, the framework is presented for unsupervised change detection using multitemporal sar images based on integration clustering and level set methods. spatial correlation between pixels were considered by using contextual information. also as proposed method was used integration of gustafson-kessel clustering techniques (gkc) and level set methods for change detection. using clust...

Fuzzy clustering methods are conveniently employed in constructing a fuzzy model of a system, but they need to tune some parameters. In this research, FCM is chosen for fuzzy clustering. Parameters such as the number of clusters and the value of fuzzifier significantly influence the extent of generalization of the fuzzy model. These two parameters require tuning to reduce the overfitting in the...

multi-path is favorite alternative for sensor networks, as it provides an easy mechanism to distributetraffic, as well as considerate fault tolerance. in this paper, a new clustering based multi path routingprotocol namely ecrr (energy efficient cluster based routing algorithm for improving reliability) isproposed, which is a new routing algorithm and guarantees the achievement to required qos ...