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An Optimization Genetic Algorithm for Image Databases in Agriculture

  • Changwu Zhu
  • Guanxiang Yan
  • Zhi Liu
  • Li Gao
Conference paper
Part of the The International Federation for Information Processing book series (IFIPAICT, volume 259)

Data Mining is rapidly evolving areas of research that are at the intersection of several disciplines, including statistics, databases, pattern recognition, and high-performance and parallel computing. In this paper, we propose a novel mining algorithm, called ARMAGA (Association rules mining Algorithm based on a novel Genetic Algorithm), to mine the association rules from an image database, where every image is represented by the ARMAGA representation. We first take advantage of the genetic algorithm designed specifically for discovering association rules. Second we propose the Algorithm Compared to the algorithm in, and the ARMAGA algorithm avoids generating impossible candidates, and therefore is more efficient in terms of the execution time.

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Copyright information

© IFIP International Federation for Information Processing 2008

Authors and Affiliations

  • Changwu Zhu
    • 1
  • Guanxiang Yan
    • 2
  • Zhi Liu
    • 3
  • Li Gao
    • 1
  1. 1.Department of Computer ScienceHua Zhong Normal UniversityChina
  2. 2.School of Information ManagementWuhan UniversityChina
  3. 3.Wuhan Junxie Shiguan SchoolChina

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