基于知识和模糊神经网络的学习型评价系统

Learning evaluation system based on knowledge and fuzzy neural networks

提出一种学习型评价系统的建立方法.评价功能是基于决策者(专家)的知识和模糊神经网络实现的,适用于以语言型变量为主的系统的评价问题.样本数据集的建立及语言型变量的描述,是通过挖掘专家知识,建立符合其偏好的隶属函数实现的.该评价系统可以充分利用以往的决策案例,通过学习获取决策者的知识和经验,从而得到与决策者的评价结论相同的评价结果.

In this paper, a method of building an evaluation system with learning ability is presented. The evaluation system is realized based on the decisionmakers' knowledge and the fuzzy neural networks, and suitable for the problems in which most variables are linguistic variables. Samples used in the developed system are mined from decisionmakers', and the corresponding membership functions are obtained by concerning with the preferences of the decisionmakers'. The developed evaluation system is capable of using the previous decision experience and extracting the knowledge from real decision examples. By training the fuzzy neural networks, the same evaluating results as the decisionmakers' can be obtained.