clustering is one of the known techniques in the field of data mining where data with similar properties is within the set of categories. k-means algorithm is one the simplest clustering algorithms which have disadvantages sensitive to initial values of the clusters and converging to the local optimum. in recent years, several algorithms are provided based on evolutionary algorithms for cluster...

Clustering is the task of automatically gathering observations into homogeneous groups, where number groups unknown. Through its basis in a statistical modeling framework, model-based clustering provides principled and reproducible approach to clustering. In contrast heuristic approaches, allows for robust approaches parameter estimation objective inference on clusters, while providing solution...

Nowadays, the Fuzzy C-Means method has become one of the most popular clustering methods based on minimization of a criterion function. However, the performance of this clustering algorithm may be significantly degraded in the presence of noise. This paper presents a robust clustering algorithm called Bilateral Weighted Fuzzy CMeans (BWFCM). We used a new objective function that uses some k...

vehicular ad-hoc network (vanet) is an important component of intelligent transportation systems, in which vehicles are equipped with on-board computing and communication devices which enable vehicle-to-vehicle communication. consequently, with regard to larger communication due to the greater number of vehicles, stability of connectivity would be a challenging problem. clustering technique as ...

We propose a framework based on Hierarchical Clustering (HC) to perform multiagent negotiations where we can specify the type of agreements needed in terms of utility sharing among the agents.The proposed multi-round mediation process is based on the analysis of the agents’ offers at each negotiation round and the generation of a social contract at each round as a feedback to the agents, which ...