Development of a Tw-norm based Novel Fuzzy Regression Model


  • B. Pushpa 1. Research Scholar, Manonmaniam Sundaranar University. Tirunelveli, India. 2. Department of Mathematics, Panimalar Institute of Technology, Chennai, India.
  • S. Muruganandam Department of Mathematics, SRM-TRP Engineering College, Trichy, India


Weakest t-norm, Fuzzy regression, Symmetric difference


The weakest t-norm (Tw-norm) based novel fuzzy regression model is developed using the concept of symmetric difference.  The proposed model will be useful in a realistic environment and improve upon the traditional fuzzy regression. The traditional system usually adopts alpha cut operations for its calculations.  Here the Tw- norm based operations are used, to reduce the width of the estimated responses which will give exact prediction. Fuzzy linear regression analysis can be seen as an optimization problem where the aim is to derive a model which fits the given dataset.  The proposed fuzzy regression analysis uses the extended objective function which is insensitive to the outlier data and the performance of the method is illustrated with different examples.



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How to Cite

Pushpa, B., & Muruganandam, S. (2013). Development of a Tw-norm based Novel Fuzzy Regression Model. Asian Journal of Fuzzy and Applied Mathematics, 1(4). Retrieved from