• DocumentCode
    3584964
  • Title

    Trend cluster analysis using self organizing maps

  • Author

    Amin, Mohd Nasir Mat ; Nohuddin, Puteri N. E. ; Zainol, Zuraini

  • Author_Institution
    Dept. of Comput. Sci., Nat. Defense Univ. of Malaysia, Kuala Lumpur, Malaysia
  • fYear
    2014
  • Firstpage
    80
  • Lastpage
    84
  • Abstract
    Trend cluster analysis using Self Organization Maps (SOM) is an application for clustering time series data. The application is able to cluster and display the time series data into trend lines graphs, and also identify trend variations in time series data. The system can process a large number of records as well as a smaller datasets. The results generated by the application are useful for analyzing large data which is often hard to analyze using normal spreadsheet software. The system has been developed using Matlab SOM functions and adopted SOM learning technique to cluster time series data. Based on the experiments, the test results have shown that the application is able to accommodate large sets of data and produce the trend lines graphs.
  • Keywords
    learning (artificial intelligence); pattern clustering; self-organising feature maps; spreadsheet programs; time series; Matlab SOM function; SOM learning technique; normal spreadsheet software; self organizing maps; time series data clustering; time series data trend variations; trend cluster analysis; trend line graph; Data mining; Forecasting; Market research; Organizations; Prototypes; Stock markets; Time series analysis; SOM; cluster analysis; clustering; time series; trend line;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information and Communication Technologies (WICT), 2014 Fourth World Congress on
  • Print_ISBN
    978-1-4799-8114-4
  • Type

    conf

  • DOI
    10.1109/WICT.2014.7077306
  • Filename
    7077306