APPLICATION OF FUZZY RECOGNITION TO MODEL SELECTION
Model selection relies on the attributes of models heavily. And the attributes of models may be certain or uncertain, so how to process these two kinds of attributes, and how to compare the similarity between the object problem and models in term of the attributes are the key issues in model selection. To solve the problem, a new method based on fuzzy recognition is introduced in this article. Firstly, object problem and models are processed by using fuzzy theory. Then, a fuzzy similarity algorithm, which combines advantage of improved index method and that of mas-min method, is proposed to select the most appropriate model. Finally, an illustrative example is given to demonstrate validity and rationality of the method.
model selection fuzzy recognition fuzzy similarity function
Wei Peng Lei Cao Yi-hui He Junru Wei
Institute of Command Automation PLA University of Science and Technology Nanjing 210007, China Military Management Departments Nanjing Army Command College Nanjing 210045, China
国际会议
Third International Conference on Information and Computing(第三届信息与计算科学国际会议 ICIC 2010)
无锡
英文
34-37
2010-06-04(万方平台首次上网日期,不代表论文的发表时间)