摘要
为了解决在模糊线性回归分析的研究中,由模糊分析计算所带来的问题,采用基于模糊数据的一元线性回归分析的模糊极小值准则和最大贴近度准则两种方法,给出了模糊结构元求解方法,得到模糊数据线性回归分析模型系数的估计值,并利用模糊结构原理论对模糊线性回归模型的模糊误差进行估计及其的性能进行评估,建立基于结构元的模糊数据模糊回归模型并对其进行实例分析.
In order to solve the computing problems caused by fuzzy analysis in the study of fuzzy linear regression analysis, this paper used monadic linear regression analysis based on fuzzy data rule of fuzzy rule of minimum and maximum closeness those two methods, and presented the solution to the fuzzy structure element. The fuzzy data estimation of the coefficient of linear regression analysis model was obtained. By using the theory of fuzzy structure, the fuzzy error in fuzzy linear regression model was estimated and its performance was evaluated. The fuzzy data fuzzy regression model based on structural units was established and instance analysis was carried out.
出处
《辽宁工程技术大学学报（自然科学版）》
CAS
北大核心
2017年第2期210-214,共5页
Journal of Liaoning Technical University (Natural Science)
基金
国家自然科学基金项目(61350003
11401284)
关键词
模糊结构元
模糊线性回归
模糊数据
模糊极小值
贴近度
fuzzy structure element
fuzzy linear regression
fuzzy data
fuzzy minimum
closeness degree
