Abstract :
The generalized differentiability of a fuzzy-number-valued function of a real variable, as recently introduced by Bede and Gal (Fuzzy Sets and Systems, vol. 151, 2005), can be expressed by first defining a generalized Hukuhara difference and using it for the differentiability; to do so, the basic elements are the lower and upper functions which characterize the level-cuts of the fuzzy quantities i.e. functions that are monotonic over [0,1]. Using this fact, we present a (parametric) representation of fuzzy numbers and its application to the solution of fuzzy differential (initial value) equations (FDE). The representation uses a finite decomposition of the membership interval [0,1] and models the level-cuts of fuzzy numbers and fuzzy functions to obtain the formulation of a fuzzy differential equation y´=f(x,y) in terms of a set of ordinary (non fuzzy) differential equations, defined by the lower and upper components of the fuzzy-valued function f(x,y). From a computational view, the resulting ODE´s can be analyzed and solved by standard methods of numerical analysis.
Keywords :
differential equations; fuzzy set theory; initial value problems; number theory; fuzzy differential equations; fuzzy functions; fuzzy number representation; fuzzy-number-valued function; generalized Hukuhara difference; generalized LU-fuzzy derivative; initial value equations; Computer applications; Control system synthesis; Differential equations; Finance; Fuzzy sets; Fuzzy systems; Numerical analysis; Physics computing; Stochastic systems; Systems engineering and theory;