Abstract
The objective of the proposed system is to develop an adaptive iterative linear regression (ILR) based clustering for wireless sensor network. ILR classifies the initial cluster simultaneously in horizontal and vertical patterns to form two sub clusters. Among these two, the best is selected based on similarity index (SI). This selected cluster is taken as reference and the iteration continues until the convergence criteria ‘Delta’ is met. The cluster quality is evaluated using internal and external indices and then compared with existing k-means and hierarchical clustering. The performance indices confirm the supremacy of the ILR clustering.
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