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Let I be a real interval and g : I → I a continuous map.
Let I be a real interval and (f : Irightarrowmathbb{R} ) be a function.
Define omega_{0}:=frac{omega}{1-q} (2.1) and let I be a real interval containing (omega_{0}).
Let I = [ a, b ] be a real interval, let f : = ( f 1, …, f k ) : I × R n × R n → R k, g : = ( g 1, …, g k ) : I × R n × R n → R k be continuously differentiable functions.
Let I be a real interval and let (f Ito mathbb {R}) be a function such that (f(c)=f(d)=0), for some (c,din I) with (cleq d).
Let I be a real interval and consider probability measures μ on I with moments (mu_{k} = int_{I} x^{k},dmu (x)), (k = 0,1,2,ldots) , such that (mu_{0} = 1).
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where I is a real interval unbounded above.
Let (x,yin C I,E_{N})), here I is a real interval and (E_{N}) is the set of all upper semicontinuous convex normal fuzzy numbers with bounded α-level intervals.
Some definitions related to interval mathematics have been used in this paper that are as follows (Trindade et al. 2010): D1 (Interval) Let (y^{L},{text{andd}},y^{{U} in,{mathbb{R}}}) be such that (y^{L} le y^{U}.) The set (bar{y} = left{ {left. {y in,{mathbb{R}}} right|,y^{{L} le y le y^{U} } right}) is called a real interval and also shown as (bar{y} = left[ {y^{L},y^{U} } right]).
Let s be a real number in the interval ((0,beta+ 1 +frac{d}{2})).
Now, let f be a real function on an interval I ⊆ R. In the previous theorem weights p i are non-negative and considered cone C is the cone S + ( n ).
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CEO of Professional Science Editing for Scientists @ prosciediting.com