the ever severe dynamic competitive environment has led to increasing complexity of strategic decision making in giant organizations. strategy formulation is one of basic processes in achieving long range goals. since, in ordinary methods considering all factors and their significance in accomplishing individual goals are almost impossible. here, a new approach based on clustering method is pro...

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 ...

In data mining, clustering is one of the important issues for separation and classification with groups like unsupervised data. In this paper, an attempt has been made to improve and optimize the application of clustering heuristic methods such as Genetic, PSO algorithm, Artificial bee colony algorithm, Harmony Search algorithm and Differential Evolution on the unlabeled data of an Iranian bank...

with the rapid expansion of the information on the internet, recommender systems play an important role in terms of trade and research. recommender systems try to guess the user's way of thinking, using the in-formation of user's behavior or similar users and their views, to discover and then propose a product which is the most appropriate and closest product of user's interest. ...

traditional leveraging statistical methods for analyzing today’s large volumes of spatial data have high computational burdens. to eliminate the deficiency, relatively modern data mining techniques have been recently applied in different spatial analysis tasks with the purpose of autonomous knowledge extraction from high-volume spatial data. fortunately, geospatial data is considered a proper s...

Data clustering is the process of partitioning a set of data objects into meaning clusters or groups. Due to the vast usage of clustering algorithms in many fields, a lot of research is still going on to find the best and efficient clustering algorithm. K-means is simple and easy to implement, but it suffers from initialization of cluster center and hence trapped in local optimum. In this paper...

Energy constraint is the biggest challenge in wireless sensor networks because the power supply of each sensor node is a battery that is not rechargeable or replaceable due to the applications of these networks. One of the successful methods for saving energy in these networks is clustering. It has caused that cluster-based routing algorithms are successful routing algorithm for these networks....

In this work, a hierarchical ensemble of projected clustering algorithm for high-dimensional data is proposed. The basic concept of the algorithm is based on the active learning method (ALM) which is a fuzzy learning scheme, inspired by some behavioral features of human brain functionality. High-dimensional unsupervised active learning method (HUALM) is a clustering algorithm which blurs the da...