Fuzzy weighted averages and implementation of the extension principle
Fuzzy Sets and Systems
Vertex method for computing functions of fuzzy variables
Fuzzy Sets and Systems
Engineering design calculations with fuzzy parameters
Fuzzy Sets and Systems
Calculating functions of fuzzy numbers
Fuzzy Sets and Systems
Explicit cost bounds of algorithms for multivariate tensor product problems
Journal of Complexity
Fuzzy arithmetic with requisite constraints
Fuzzy Sets and Systems - Special issue: fuzzy arithmetic
A parametric representation of fuzzy numbers and their arithmetic operators
Fuzzy Sets and Systems - Special issue: fuzzy arithmetic
Fuzzy Sets and Systems: Theory and Applications
Fuzzy Sets and Systems: Theory and Applications
The transformation method for the simulation and analysis of systems with uncertain parameters
Fuzzy Sets and Systems - Fuzzy intervals
Algorithm 847: Spinterp: piecewise multilinear hierarchical sparse grid interpolation in MATLAB
ACM Transactions on Mathematical Software (TOMS)
Algorithm 847: Spinterp: piecewise multilinear hierarchical sparse grid interpolation in MATLAB
ACM Transactions on Mathematical Software (TOMS)
Simulation of discrete linear time-invariant fuzzy dynamic systems
Fuzzy Sets and Systems
Finite Elements in Analysis and Design
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Fuzzy arithmetic provides a powerful tool to introduce uncertainty into mathematical models. With Zadeh's extension principle, one can obtain a fuzzy extension of any objective function. Computing expensive multivariate functions of fuzzy numbers, however, often poses a difficult problem due to non-applicability of common fuzzy arithmetic algorithms, severe overestimation, or very high computational complexity. This paper proposes a new approach based on sparse grids, consisting of two parts: First, we compute a surrogate function using sparse grid interpolation. Second, we perform the fuzzy-valued evaluation of the surrogate function by a suitable implementation of the extension principle based on real or interval arithmetic. The new approach gives accurate results and requires only few function evaluations.