摘要
模糊知识表示及处理是人工智能中的重要研究课题之一,模糊知识的匹配是进行模糊知识推理的关键。通过对传统的各种不同的模糊匹配方法的探讨,提出了一种改进的模糊知识匹配方法——IDM(Inscribed Diameter Matching)法。通过比较分析得出,IDM法能较好地克服传统的模糊匹配方法的一些缺点,并给出了一种融合模型,由此可使模糊推理的效率和准确性得到提高。最后,通过实例验证了IDM方法的可行性和有效性。
The expression and treatment of fuzzy knowledge is one of the important research subject in artificial intelligence field. Fuzzy knowledge matching is the key to going along fuzzy knowledge reasoning. Through discussing various traditional fuzzy matching method, came up with an improved method of fuzzy knowledge matching- IDM（inscribed diameter matching）. From comparative analysis, gained the result： IDM method can well conquer some disadvantage of traditional fuzzy matching method, and put forward a kind of integration model,which can improve efficiency and accuracy of fuzzy knowledge inference. Finally, verified the feasibility and effectiveness of IDM method using instance.
出处
《计算机技术与发展》
2008年第8期140-143,F0003,共5页
Computer Technology and Development
基金
云南省自然科学基金重点项目(04F00062)
江苏技术师范学院青年科研基金项目(KYY07057)
关键词
模糊知识匹配
匹配程度
IDM法
fuzzy knowledge matching
matching degree
IDM method
