摘要
提出了一种基于语言神经网络的知识获取方法,该方法利用语言神经元,对具有开区域的连续输入变量,自动产生相应的语言变量输出,讨论了相应的神经网络训练和知识获取方法,所获取的知识以If-Then的规则形式表示,具有简洁、紧凑、不必进一步化简、易于理解等特点,并给出在智能教学系统中获取专家领域知识的应用实例.
A new methodology of extracting rules from linguistic neural networks is proposed. A linguistic neural unit, which has the ability to analyze continuous input variables in open districts and produces corresponding linguistic variables, is described. The training method for network with linguistic neural layer is discussed. The rules extracted are represented in concise and comprehensible If-Then forms, and don't need to be simplified further. An example showing how to extract rules automatically from the expert domain knowledge for intelligent tutoring system (ITS) is given.
出处
《系统工程理论与实践》
EI
CSCD
北大核心
2004年第2期68-73,115,共7页
Systems Engineering-Theory & Practice
基金
广西民族学院归国留学人员科研启动基金(0098WDX00061)
关键词
神经网络
语言神经元
规则获取
智能教学系统
neural network
linguistic neural units
extracting rules
intelligent tutoring system
