WASET
	@article{(Open Science Index):https://publications.waset.org/pdf/10003945,
	  title     = {A Fuzzy Linear Regression Model Based on Dissemblance Index},
	  author    = {Shih-Pin Chen and  Shih-Syuan You},
	  country	= {},
	  institution	= {},
	  abstract     = {Fuzzy regression models are useful for investigating
the relationship between explanatory variables and responses in fuzzy
environments. To overcome the deficiencies of previous models and
increase the explanatory power of fuzzy data, the graded mean
integration (GMI) representation is applied to determine
representative crisp regression coefficients. A fuzzy regression model
is constructed based on the modified dissemblance index (MDI),
which can precisely measure the actual total error. Compared with
previous studies based on the proposed MDI and distance criterion, the
results from commonly used test examples show that the proposed
fuzzy linear regression model has higher explanatory power and
forecasting accuracy.},
	    journal   = {International Journal of Mathematical and Computational Sciences},
	  volume    = {8},
	  number    = {9},
	  year      = {2014},
	  pages     = {1278 - 1283},
	  ee        = {https://publications.waset.org/pdf/10003945},
	  url   	= {https://publications.waset.org/vol/93},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 93, 2014},
	}