高等学校化学学报

高等学校化学学报 ›› 2001, Vol. 22 ›› Issue (11): 1813.

• 研究论文 • 上一篇    下一篇

一类基于模糊神经元的复杂非线性化学模式识别方法

程翼宇, 赵明洁   

  1. 浙江大学化学工程与生物工程学系、制药工程研究所, 杭州 310027
  • 收稿日期:2000-10-30 出版日期:2001-11-24 发布日期:2001-11-24
  • 通讯作者: 程翼宇(1958年生),男,博士,教授,博士生导师,主要从事化学信息学与药物学等研究.
  • 基金资助:

    国家重点基础研究发展规划(973计划编号G1999054405);国家自然科学基金(批准号:39870940)资助

A Type of Fuzzy Classification Neural Networks for Complex Nonlinear Chemical Pattern Recognition

CHENG Yi-Yu, ZHAO Ming-Jie   

  1. Department of Chemical Engineering Bioengineering, Institute of Pharmaceutical Engineering, Zhejiang University, Hangzhou 310027, China
  • Received:2000-10-30 Online:2001-11-24 Published:2001-11-24

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被引次数

18

摘要： 针对模式类别边界曲折而模糊的复杂化学模式分类问题,提出一种化学模式模糊分类方法,并给出其模糊神经元分类器设计和网络训练算法,使模糊神经元分类器具有学习功能.以一个应用实例检验了该方法的实效.

关键词: 复杂化学模式识别, 模糊模式分类, 模糊神经元分类器

Abstract: For a type of classification problems of complex chemical patterns, in which the edges between pattern classes are rather irregular or ill defined, a new fuzzy computing method for chemical pattern classification is proposed. The new method was realized with a fuzzy neural network. An algorithm for training the fuzzy neural networks, which makes the fuzzy pattern classifier has the ability of learning from examples, is given. An example of classifying complex chemical pattern was used to verify the efficiency of the new method.

Key words: Complex chemical pattern recognition, Fuzzy pattern classification, Fuzzy neural classifier

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