Question

英文摘要翻译（是我的毕业论文摘要，请不要用翻译工具翻译，谢谢）

摘要：在许多实际问题中，训练数据的作用是不同的，通常有些训练数据比其他数据可能更重要。刻画每组训练数据的不同作用通常是通过给每个训练数据赋予一个置信权重来实现的，基于这样的模糊数据，本文还重新推导了经典的回归方法，以及在此相对情况下的模糊回归方法，并且分析了他们的统计性质。在模糊统计分析中求置信权重的传统方法是由设定的模糊隶属函数来确定的，如时间序列函数等。考虑到DEA分析方法在评价决策单元的相对有效性上有着不可低估的优越性，那么我们把DEA方法引进模糊统计分析中，与通常用的模糊隶属函数所确定的置信权重方法作比较，体现DEA分析方法在模糊统计领域中也具有优越性。 关键词：DEA分析方法；最小二乘回归分析；模糊统计；

Answer 1

Abstract: in many practical problems, the training data is different, usually some training data may be more important than other data. Each group of training data depict different function is usually through each training data gives an incredible weights, based on the fuzzy data, this paper has deduced the classic again in the regression method, and the relative cases of fuzzy regression method, and analyzed their statistical properties. In fuzzy statistic analysis of the traditional methods are incredibly weight by setting the fuzzy membership functions, such as to determine the time sequence function etc. Considering the DEA method in the analysis of the relative effectiveness evaluation decision unit has not underestimate the superiority of the DEA method, then we introduce fuzzy statistic analysis, and usually use the fuzzy membership functions of the incredible weight determined comparing method, fuzzy statistic analysis method in DEA model is superior. Keywords: DEA analysis method, Least-squares regression analysis, Fuzzy statistic,