In this paper, we have shown that the fuzzy-rough set attribute reduction algorithm [Jenson, R., Shen, Q., 2002. Fuzzy-rough sets for descriptive dimensionality reduction. In: Proceedings of IEEE International Conference on Fuzzy Systems, FUZZ-IEEE'02, May 12-17, pp. 29-34] is not convergent on many real datasets due to its poorly designed termination criteria; and the computational complexity ...

Establishing innovation alliance has now become a very important and indispensable way for achieving the mission of research and development (R&D) of national mega projects in China. As an important component for constructing the collaborative partnership system, an appropriate approach of partner selection should be able to evaluate the performance of candidates objectively. Innovation allianc...

We interpret fuzzy multiple objective linear programming (FMOLP) problems with fuzzy coefficients and fuzzy inequality relations as multiple fuzzy reasoning schemes (MFR), where the antecedents of the scheme correspond to the constraints of the FMOLP problem and the facts of the scheme are the objectives of the FMOLP problem. Then the solution process consists of two steps: first, for every dec...

the main objective of this study was to arak city zoning geomorphological parameters of the model using fuzzy logic. in order to realize these objectives, 10 parameters including of height, distance from fault, distance from the main channel, distance from sub-channel, distance from road, slope percent, distance from settlements, terrain type, erosion potential and seismic vulnerability in the ...

g e y w o r d s F u z z y numbers, Convexity, Continuity, Convex fuzzy mappings, Linear ordering, Fuzzy Weirstrass theorem, Fuzzy optimization. 1. I N T R O D U C T I O N Let R n denote the n-dimensional Eucl idean space. The suppor t , supp(#) , of a fuzzy set # : R ~ I = [0, 1] is defined as supp(/~) = {x • R n I #(x) > 0}. A fuzzy set # : R n --~ I is called fuzzy convex if #(Ax + (1 A)y) _>...

We derive an explicit expression for an associative ∗-product on the fuzzy complex projective space, CPN−1 F . This generalises previous results for the fuzzy 2-sphere and gives a discrete non-commutative algebra of functions on CPN−1 F , represented by matrix multiplication. The matrices are restricted to ones whose dimension is that of the totally symmetric representations of SU(N). In the li...

We consider space and time dependent fuzzy spheres S 2p arising in D1 − D(2p + 1) intersections in IIB string theory and collapsing D(2p)-branes in IIA string theory. In the case of S 2 , where the periodic space and time-dependent solutions can be described by Jacobi elliptic functions, there is a duality of the form r to 1 r which relates the space and time dependent solutions. This duality i...

We consider space and time dependent fuzzy spheres S 2p arising in D1 − D(2p + 1) intersections in IIB string theory and collapsing D(2p)-branes in IIA string theory. In the case of S 2 , where the periodic space and time-dependent solutions can be described by Jacobi elliptic functions, there is a duality of the form r to 1 r which relates the space and time dependent solutions. This duality i...

The COCOMO Model is well known as the currently predominate model for software cost estimation. It allows one to work from linguistic variables to estimate software project effort and schedule. This basis in linguistic variables encourages research of the COCOMO Model as a fuzzy system. As is known in fuzzy circles and is shown here, fuzzy arithmetic based on the popular fuzzy extension princip...

The purpose of this paper is to propagate the input uncertainties of the degree-day method to estimate the building heating energy consumption as numerical intervals. While it is common to use average or expected values (e.g., Typical Meteorological Year) to address the input uncertainties, this practice can only yield the best estimates as single-point values without informing the possible ran...