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文章基本信息

  • 标题:Neural Network Fuzzy Learning Vector Quantization (FLVQ) to Identify Probability Distributions
  • 本地全文:下载
  • 作者:Warsono ; Gerry Alfa D ; Dian Kurniasari
  • 期刊名称:International Journal of Computer Science and Network Security
  • 印刷版ISSN:1738-7906
  • 出版年度:2016
  • 卷号:16
  • 期号:10
  • 页码:16-19
  • 出版社:International Journal of Computer Science and Network Security
  • 摘要:A Statistical model is built based on a probability distribution. Classically, probability distribution is identified by some methods for example by using Chi-square goodness of fits, by using graph, by nonparametric goodness of fits test, and by using normal plot to test the normality. The aim of this study is going to discuss the applications of Fuzzy Learning Vector Quantization (FLVQ) model to identify some probability distributions this model is a merger between neural network and fuzzy set. The results from the application of this FLVQ through a simulation to identify the probability distributions are very good and can be implemented to a real data.
  • 关键词:neural network; fuzzy set; FLVQ; codebook vector; goodness of fits test
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