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In this paper, based on least trimmed squares-support vector regression (LTS-SVR), a robust radial basis function network (RRBFN) is proposed in the modeling problem to deal with training data sets that may contain outliers and noises. There are two stages in the proposed RRBFN approach. In stage I, outliers and large noises will be trimmed via the LTS-SVR procedure so that the influences of outliers...
Recognizing relatively smaller classes (called imbalanced classes) from data is an important task both from a theoretical and practical points of view. In many real world problems smaller classes are usually more interesting from the user point of view but they are more difficult to obtain by a classifier. This paper, which is a continuation of our previous works, discusses a classifier that is based...
In recent years, several attempts to improve the efficiency of the Canonical Genetic Algorithm have been presented. The advantage of the elitist non-homogeneous genetic algorithm is that variation of the mutation probabilities permits the algorithm to broaden its search space at the start and restrict it later on, however the way in which the mutation probabilities vary is defined before the algorithm...
As an emerging computing paradigm of information processing, Granular Computing exhibits great potential in human-centric decision problems such as feature selection and feature extraction, pattern recognition and knowledge discovery. Optimization plays an important role in these areas. The optimization problems arising in Granular Computing area are called granular optimization problems in which...
This paper presents a new optimization algorithm based on quantum-inspired evolutionary techniques that simultaneously incorporates two important features: (i) the treatment of multiple objectives and (ii) the treatment of related categorical attributes, applicable to a specific form of combinatorial optimization. The proposed optimization algorithm is applied to the development of fuzzy inference...
This paper investigates the dimensions of ℒ-semilinear subspaces of Vn. It first obtains some necessary and sufficient conditions that each basis has the same number of elements. Then it presents that over some zerosumfree semirings, each basis also has the same number of elements. In the end, it discusses the relationships between the direct sums and the dimensions of semilinear subspaces of n-dimensional...
Based on a frame L, fuzzy posets make a good framework of quantitative domain theory. In this paper, we propose the definition of locally order preserving functors between the categories of fuzzy directed-complete posets and show that these functors can preserve adjointness, surjectivity and injectivity of maps having an adjoint.
We investigate relationships between fuzzy sets and some variants of α-cuts (so called f-cuts) in sets with similarity relations, with values in a complete residuated lattice Ω (so called Ω-sets), which are objects of two special categories Set(Ω) and SetR(Ω). We prove that these relationships can be expressed as natural isomorphisms between covariant and contravariant functors representing fuzzy...
This paper presents a summarized characterization of embedded type-1 fuzzy sets (ET1FS) by using the classical concept of convex combination given by Zadeh. ET1FSs are important when defining the centroid of an interval-valued fuzzy set (IVFS) and some type-reduction methods proposed in the literature. We will show that any ET1FS of an IVFS, with no assumption whatsoever about the universal set (either...
We introduce a new class of non-standard fuzzy subsets called Pythagorean fuzzy subsets and the related idea of Pythagorean membership grades. We focus on the negation operation and its relationship to the Pythagorean theorem. We compare Pythagorean fuzzy subsets with intuitionistic fuzzy subsets. We look at the basic set operations for the Pythagorean fuzzy subsets.
The main goal of this paper is to investigate the properties of fuzzy ideals of a ring R. It provides a proof that there exists an isomorphism of lattices of fuzzy ideals when ever the rings are isomorphic. Finite-valued fuzzy ideals are also described and a method is created to count the number of fuzzy ideals in finite and Artinian rings.
We discuss how the specifics of data granulation methodology can influence Infobright's database system performance. We put together our two previous research paths related to machine-generated data sets, namely, dynamic reorganization of data during load and efficient handling of alphanumeric columns with compound values. We emphasize the role of domain knowledge while tuning data granulation processes.
Subgroup Discovery (SD) is a data mining technique whose main objective is the search for descriptions of subgroups of data that are statistically unusual with respect to a property of interest. General rules describing as many instances as possible are preferred in SD, but this can lead to less accurate descriptions that incorrectly describe some instances. These negative examples can be grouped...
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