Geodesic
In Regular Intervals Fuzzy Model of Linear Regression
Sibirskij žurnal čistoj i prikladnoj matematiki, Tome 10 (2010) no. 2, pp. 118-134

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In this paper the fuzzy and ordinary model in the case of simple linear regression is studied. The geometrical interpretation of fuzzy model and its comparing with ordinary model of simple linear regression are given. The computing complexity of fuzzy model of linear regression is investigated. The effective algorithms of the decision having complexity of the orders $O (n\log n) $, $O (n^2) $, and their realization in MatLab are indicated.
Keywords: fuzzy linear regression model, computational complexity. 
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     author = {I. V. Ponomarev and V. V. Slavsky},
     title = {In {Regular} {Intervals} {Fuzzy} {Model} of {Linear} {Regression}},
     journal = {Sibirskij \v{z}urnal \v{c}istoj i prikladnoj matematiki},
     pages = {118--134},
     publisher = {mathdoc},
     volume = {10},
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     year = {2010},
     language = {ru},
     url = {http://geodesic.mathdoc.fr/item/VNGU_2010_10_2_a9/}
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I. V. Ponomarev; V. V. Slavsky. In Regular Intervals Fuzzy Model of Linear Regression. Sibirskij žurnal čistoj i prikladnoj matematiki, Tome 10 (2010) no. 2, pp. 118-134. http://geodesic.mathdoc.fr/item/VNGU_2010_10_2_a9/