DRID- A New Merging Approach

Merging of clusters is a deterministic approach which provides results in an efficient manner. It involves the data input values as per the suitability of the algorithm. There are various advantages for merging of clusters like to improve the quality of clusters, to reduce the noise level and to increase the performance of the algorithm. Merging of clusters is possible in any environment it totally depends on the availability of the type of dataset values. In this paper, we propose an algorithm for merging of cluster. This proposed algorithm merges the clusters which is placed near by to each other because of Cluster balancing is a key factor to achieve good performance. The performance of DRID heavily depends on the dataset availibity and type of environment used by the user. The crucial step in this algorithm is how to select the best and next cluster for merging and splitting.Experimental results and comparisons actually demonstrate that the proposed DRID is an effective approach which helps to reduce execution time and increase the overall performance of the algorithm