clustering technique is one of the most important techniques of data mining and is the branch of multivariate statistical analysis and a method for grouping similar data in to same clusters. with the databases getting bigger, the researchers try to find efficient and effective clustering methods so that they can make fast and real decisions. thus, in this paper, we proposed an improved ant syst...

knowing the fact that the main weakness of the most standard methods including k-means and hierarchical data clustering is their sensitivity to initialization and trapping to local minima, this paper proposes a modification of convex data clustering  in which there is no need to  be peculiar about how to select initial values. due to properly converting the task of optimization to an equivalent...

In order to overcome the shortcomings of traditional clustering algorithms such as local optima and sensitivity to initialization, a new Optimization technique, Particle Swarm Optimization is used in association with Unsupervised Clustering techniques in this paper. This new algorithm uses the capacity of global search in PSO algorithm and solves the problems associated with traditional cluster...

We propose a new version of a multiobjective coevolutionary algorithm. The main idea of the proposed approach is to concentrate the search effort on promising regions that arise during the evolutionary process as a product of a clustering mechanism applied on the set of decision variables corresponding to the known Pareto front. The proposed approach is validated using several test functions ta...

Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...

Assigning a set of objects to groups such that objects in one group or cluster are more similar to each other than the other clusters’ objects is the main task of clustering analysis. SSPCO optimization algorithm is anew optimization algorithm that is inspired by the behavior of a type of bird called see-see partridge. One of the things that smart algorithms are applied to solve is the problem ...

Swarm Intelligence (SI) is an innovative artificial intelligence technique for solving complex optimization problems. Data clustering is the process of grouping data into a number of clusters. The goal of data clustering is to make the data in the same cluster share a high degree of similarity while being very dissimilar to data from other clusters. Clustering algorithms have been applied to a ...

this paper proposes the exchange market algorithm (ema) to solve the combined economic and emission dispatch (ceed) problems in thermal power plants. the ema is a new, robust and efficient algorithm to exploit the global optimum point in optimization problems. existence of two seeking operators in ema provides a high ability in exploiting global optimum point. in order to show the capabilities ...