An Effective Performance of Fuzzy Hierarchical Clustering Using Time Series Data Streams

  • V.Kavitha
  • M.Punithavalli
Part of the Communications in Computer and Information Science book series (CCIS, volume 142)


Mining Time Series data has a remarkable development of concentration in today’s humanity. Clustering time series is a trouble that has applications in a wide variety of fields and has recently fascinated a huge amount of researchers. Time series data are frequently large and may surround outliers. In addition, time series are a special type of data set where elements have a chronological ordering. Therefore clustering of such data stream is an important issue in the data mining process. The clustering algorithms and its effectiveness on various applications are compared to extend an innovative method to solve the existing problem. This paper presents a new method called Fuzzy Hierarchical clustering algorithm is implemented. Experimental results on ECG data evaluate the processing qualities of the system is more accurate than the previous system.


Time Series Data Streams Hierarchical Clustering Fuzzy Logic 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • V.Kavitha
    • 1
  • M.Punithavalli
    • 2
  1. 1.Dept of Computer ScienceKarpagam UniversityCoimbatoreIndia
  2. 2.Dr.SNS Rajalakshmi College of Arts and ScienceCoimbatoreIndia

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