Robust Fuzzy Varying Coefficient Regression Analysis with Crisp Inputs and Gaussian Fuzzy Output

نویسندگان

  • Zhihui Yang
  • Yunqiang Yin
  • Yizeng Chen
چکیده

This study presents a fuzzy varying coefficient regression model after deleting the outliers to improve the feasibility and effectiveness of the fuzzy regression model. The objective of our methodology is to allow the fuzzy regression coefficients to vary with a covariate, and simultaneously avoid the impact of data contaminated by outliers. In this paper, fuzzy regression coefficients are represented by Gaussian fuzzy numbers. We also formulate suitable goodness of fit to evaluate the performance of the proposed methodology. An example is given to demonstrate the effectiveness of our methodology. Category: Smart and intelligent computing

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Two-Parameters Fuzzy Ridge Regression with Crisp Input and Fuzzy Output

‎In this paper a new weighted fuzzy ridge regression method for a given set of crisp input and triangular fuzzy output values is proposed‎. ‎In this regard‎, ‎ridge estimator of fuzzy parameters is obtained for regression model and its prediction error is calculated by using the weighted fuzzy norm of crisp ridge coefficients‎. . ‎To evaluate the proposed regression model‎, ‎we introduce the fu...

متن کامل

A New Algorithm for Fuzzy Linear Regression with Crisp Inputs and Fuzzy Output

In this work, the parameters of fuzzy linear regression based on the least squares approach is computed by ST-decomposition method. This method is not an iterative technique, however, it is a powerful method for nonsingular coefficient matrices. Numerical examples are at the end of this paper to illustrate the performance of the new method.

متن کامل

Linear regression analysis for fuzzy/crisp input and fuzzy/crisp output data

In order to estimate fuzzy regression models, possibilistic and least-squares procedures can be considered. By taking into account a least-squares approach, regression models with crisp or fuzzy inputs and crisp or fuzzy output are suggested. In particular, for these fuzzy regression models, unconstrained and constrained (with inequality restrictions) least-squares estimation procedures are dev...

متن کامل

Fuzzy Linear Regression Models with Fuzzy Entropy

Fuzzy regression analysis using fuzzy linear models with symmetric triangular fuzzy number coefficient has been introduced by Tanaka et al. The goal of this regression is to find the coefficient of a proposed model for all given input-output data sets. In this paper, we propose a new 1716 E. Pasha et al method for computation of fuzzy regression. The method is constructed on the basis of minimi...

متن کامل

Two-stage DEA with Fuzzy Data

Data envelopment analysis is a nonparametric technique checking efficiency of DMUs using math programming. In conventional DEA, it has been assumed that the status of each measure is clearly known as either input or output. Kao and Hwang (2008) developed a data envelopment analysis (DEA) approach for measuring efficiency of decision processes which can be divided into two stages. The first stag...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:
  • JCSE

دوره 7  شماره 

صفحات  -

تاریخ انتشار 2013