Trend detection on thin-film solar cell technology using cluster analysis and modified data crystallization

  • Authors:
  • Tzu-Fu Chiu;Chao-Fu Hong;Yu-Ting Chiu

  • Affiliations:
  • Department of Industrial Management and Enterprise Information, Aletheia University, Taiwan, R.O.C.;Department of Information Management, Aletheia University, Taiwan, R.O.C.;Department of Information Management, National Central University, Taiwan, R.O.C.

  • Venue:
  • ICCCI'10 Proceedings of the Second international conference on Computational collective intelligence: technologies and applications - Volume PartI
  • Year:
  • 2010

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Abstract

Thin-film solar cell, one of green energies, is growing at a fast pace with its long-lasting and non-polluting natures. To detect the potential trends of this technology is essential for companies and relevant industries so that the competitive advantages of companies can be retained and the developing directions of industries can be perceived. Therefore, a research framework for trend detection has been formed where cluster analysis is employed to perform the similarity measurement, and data crystallization is adopted to conduct the association analysis. Consequently, the relation patterns were identified from the relations among companies, issue years, and techniques. Finally, according to the relation patterns, the potential trends of thin-film solar cell were detected for companies and industries.