The proposed work represents ranking based method that improved K-means clustering algorithm performance and accuracy. In this we have also done analysis of K-means clustering algorithm, one is the existing Kmeans clustering approach which is incorporated with some threshold value and second one is ranking method which is weighted page ranking applied on K-means algorithm, in weighted page rank...

Clustering is one of the unsupervised learning method in which a set of essentials is separated into uniform groups. The k-means method is one of the most widely used clustering techniques for various applications. This paper proposes a method for making the K-means algorithm more effective and efficient; so as to get better clustering with reduced complexity. In this research, the most represe...

Clustering is an unsupervised process that divides a given set of objects into groups so that objects within a cluster are highly similar with one another and dissimilar with the objects in other clusters. In this article, a new clustering method based on cat swarm optimization was proposed to find the proper clustering of data sets called K-means improvement and Simulated Annealing selection b...

Pyrite oxidation, Acid Rock Drainage (ARD) generation, and associated release and transport of toxic metals are a major environmental concern for the mining industry. Estimation of the metal loading in ARD is a major task in developing an appropriate remediation strategy. In this study, an expert system, the Multi-Output Adaptive Neuro-Fuzzy Inference System (MANFIS), was used for estimation of...