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ISSN Print: 2394-7500, ISSN Online: 2394-5869, CODEN: IJARPF

Impact Factor: RJIF 5.2

International Journal of Applied Research

Vol. 2, Issue 7, Part A (2016)

A comparative study of fuzzy multiple regression model and least square method

Author(s)
Ubale AB, Sananse SL
Abstract
The objectives of this study is to formulate a multiple fuzzy linear regression model using crisp input/output to investigate the relationship between explanatory and response variables to estimate the model parameters. For present study, fuzzy linear regression model proposed by Zadeh’sis used which is based on fuzzy linear function. Comparative study of fuzzy multiple regression model and conventional multiple regression model is done on the basis of coefficient of determination which is used as goodness of fit for both the models. Finally, a numerical example is provided for demonstration of the results. It is observed that the fuzzy multiple regression model is more suitable than the conventional multiple regression model resulting in higher coefficient of determination.
Pages: 11-15  |  595 Views  24 Downloads
How to cite this article:
Ubale AB, Sananse SL. A comparative study of fuzzy multiple regression model and least square method. International Journal of Applied Research. 2016; 2(7): 11-15.
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International Journal of Applied Research