计算机应用 ›› 2010, Vol. 30 ›› Issue (4): 1089-1092.

• 数据库与数据挖掘 • 上一篇    下一篇

基于自适应直觉模糊推理的数据挖掘方法

吕大江1,石志寒2,雷英杰2,张国锁2   

  1. 1. 空军工程大学导弹学院研究生三队
    2.
  • 收稿日期:2009-09-15 修回日期:2009-11-20 发布日期:2010-04-15 出版日期:2010-04-01
  • 通讯作者: 吕大江
  • 基金资助:
    直觉模糊集理论及其应用研究

Data mining method based on adaptive intuitionistic fuzzy inference

  • Received:2009-09-15 Revised:2009-11-20 Online:2010-04-15 Published:2010-04-01

摘要: 针对数据挖掘问题,将直觉模糊集与神经网络理论相结合,提出一种新的方法。用自适应直觉模糊推理的方法来解决数据挖掘问题,该方法可以根据直觉模糊神经网络本身的自适应学习能力来调节网络参数,自动生成规则库。最后通过一个仿真实例证明了该方法的有效性。

关键词: 直觉模糊推理, 神经网络, 自适应, 训练, 规则

Abstract: A new method was proposed for data mining problem which integrated intuitionistic fuzzy set and neural network theory. This article solved the data mining problem with the method of adaptive intuitionistic fuzzy inference. This method can adjust network variables by use of intuitionistic neural networks adaptive learning function, and generate rules bank automatically. Finally, this method was validated by simulation.

Key words: intuitionistic fuzzy inference, neural network, adaptive, train, rule