Hybrid Fuzzy Regression Analysis Using the F-Transform

This paper proposes a hybrid estimation algorithm for independently estimating the response function for the center and the response function for the spread in fuzzy regression model. The proposed algorithm combines the least absolute deviations estimation with discriminant analysis. In addition, the F-transform is used to convert spreads of the dependent variable into several groups. Two examples show that our method is superior to the existing methods based on the fuzzy regression model that assumes the same function for spread and center.

Diagnostic Analytics on Agriculture with Fuzzy Classification

Agriculture is the main domain and need of India. The country is second place in the world in agriculture. Cropping is the main part of agriculture. Various crops like millets, fruits, vegetables, oil seeds are produced and exported to other countries every year. So, various innovative technologies are used to improve the productivity of crops in agriculture. Rainfall is most important for growing crops. The water level for the crops based on rainfall has some uncertainty. Fuzzy regression analysis is one of the methods based on regression analysis that is used to handle fuzzy parameters and crisp data and vice versa. Linear fuzzy regression is one of the methods of fuzzy regression analysis to handle fuzzy parameters. This chapter explores fuzzy classification, which is based on fuzzy regression analysis, and it is compared with other classification algorithms on the agriculture data.