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A PSO Optimized Layered Approach for Parametric Clustering on Weather Dataset

By Shikha Verma and Kiran Jyoti

Abstract

Abstract: Clustering is the process to present the data in an effective and organized way. There are number of existing clustering approaches but most of them suffer with problem of data distribution. If the distribution is non linear it gives impurities in clustering process. The propose work is about to improve the accuracy of such clustering algorithm. Here we are presenting the work on time series oriented database to present the work. Here we are presenting the three layer architecture, where first layer perform the partitioning based on time series and second layer will perform the basic clustering. The PSO is finally implemented to remove the impurities from the dataset

Topics: Clustering, CMeans, KMeans, Dataset, Feature
Year: 2014
OAI identifier: oai:CiteSeerX.psu:10.1.1.417.1653
Provided by: CiteSeerX
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