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The influence of the missing values in the classification of incomplete pattern mainly depends on the context. In this paper, we present a fast classification method for incomplete pattern based on the fusion of belief functions where the missing values are selectively (adaptively) estimated. At first, it is assumed that the missing information is not crucial for the classification, and the object...
Crowdsourcing provides a cheap but efficient approach for large-scale data and information collection. However, human judgments are inherently noisy, ambiguous and sometimes biased, and should be calibrated by additional (usually much more expensive) expert or true labels. In this work, we study the optimal allocation of the true labels to best calibrate the crowdsourced labels. We frame the problem...
The problem of selecting a template that matches a given candidate signal is applicable across a wide variety of domains. Using the correlation coefficient as the avenue for selecting the winning template is perhaps the most common technique. The challenge lies in selecting the winning template when there is no clear separation between the correlation coefficient values of the winning template and...
It is a well known fact that non-additive measures, i.e., monotone set functions, and corresponding integrals have been successfully applied in many different areas, both theoretical and practical. Due to the course of research, this problem has diversified into two directions. One direction covers real-valued set functions, while the second one leads towards the set-valued case. The first option...
In the paper the method based on order statistics for processing of the random observations with so called Flatten — Gaussian distribution that is a convolution of rectangular and normal distributions, is proposed. This method gives a smaller standard uncertainty of a location parameter compared to a standard uncertainty of a mean value. The efficiency of the method increases with the increase content...
The intuitionistic fuzzy aggregation operators play an important role in combining multidimensional information in decision making process under uncertainty and recently received much more attentions to practitioners. In this paper, the generalized intuitionistic fuzzy Einstein weighted averaging (GIFEWA) operator is proposed. Based on the developed operator, a procedure is given to deal with multi-criteria...
Mobile data traffic has surpassed that of voice to become the main component of the system load of today's wireless networks. Recent studies indicate that the data demand patterns of mobile users are predictable. Moreover, the channel quality of mobile users along their navigation paths is predictable by exploiting their location information. This work aims at fusing the statistically predictable...
TOPSIS method is a most useful tool for solving MADM problems, also, Choquet integral method is another powerful method which, is able to manage interaction criteria. In this paper, we combine both methods to use from their benefits. First, we will introduce a new method for computing the distance between IT2FSs. Then, we proposed a hybrid method based on TOPSIS and Choquet integral in fuzzy type-2...
In classification tasks, as the dimensionality increases, the performance of the classifier improves until an optimal number of features is reached. Further increases of the dimensionality without increasing the number of training samples results in a degradation in classifier performance. This fact, called the curse of dimensionality, has become more relevant with the advent of larger datasets and...
While the usual 1-D fuzzy logic has many successful applications, in some practical cases, it is desirable to come up with a more subtle way of representing expert uncertainty. A natural idea is to add additional information, i.e., to go from 1-D to 2-D (and multi-D) fuzzy logic. At present, there are two main approaches to 2-D fuzzy logic: interval-valued and complex-valued. At first glance, it may...
Race conditions in real-time systems may cause unexpected computing result. Due to the uncertainty of realtime systems, a race condition detected by many static and dynamic approaches may occur in one execution environment but may not occur in another execution environment. In this paper, an easy and practical approach based on probabilistic models is presented to analyze the uncertainties of race...
In many practical situations, we make predictions based on the measured and/or estimated values of different physical quantities. The accuracy of these predictions depends on the accuracy of the corresponding measurements and expert estimates. Often, for each quantity, there are several different sources of inaccuracy. Usually, to estimate the prediction accuracy, we first combine, for each input,...
The main study of this paper is focused on the solutions of a class of fuzzy sequential fractional differential equations in the form of (0Dxβy)′(x) = b(x)y(x), where (0Dxβy)(x) is the fuzzy Riemann-Liouville derivative of order β ∈ (0, 1). On this subject, a new fuzzy complete metric space is introduced. Finally, we proof the existence and uniqueness of our solution using the contraction principle.
In the paper properties of intuitionistic fuzzy relations are considered and preservation of some properties by operations, including lattice operations, composition and related operators are studied. Properties of intuitionistic fuzzy relations, namely reflexivity, irreflexivity, connectedness, symmetry, antisymmetry, perfect antisymmetry and transitivity are considered. Moreover, the authors study...
In computing with words, words can be modelled by interval-valued (IV) fuzzy sets (FSs). Constructing an footprint of uncertainty (FOU) for an IV FS about a word has been a critical issue. Although a number of methods have been developed, it remains challenging for each people to provide an FOU about his or her word. A primary reason is that FOUs are implicit in indicating the possibilities of the...
In this paper, we investigate the multiple attribute group decision making (MAGDM) problems based on grey system theory and utility theory to accommodate situations where attribute values take the form of interval type-2 fuzzy sets (IT2FSs). Motivated by the idea of grey incidence analysis theory, we propose two new grey incidence degrees for aggregating the uncertain information and further extend...
Clustering is a technique of unsupervised classification. The methods are classified into two types, one is hierarchical and the other is non-hierarchical. Fuzzy non-metric model (FNM) is a representative method of non-hierarchical clustering. FNM is very useful because belongingness or the membership degree of each datum to each cluster is calculated directly from dissimilarities between data, and...
Uncertainty, hesitation and vagueness are inherent to human beings when articulating opinions and preferences. Therefore in decision making situations it might well be the case that experts are unable to express their opinions in an accurate way. Under these circumstances, various families of preference relations (PRs) have been proposed (linguistic, intuitionistic and interval fuzzy PRs) to allow...
Centroid of a general type-2 (GT2) fuzzy set (FS) has been a critical concept. With the introduction of the α plane representation / the z slice representation for a GT2 FS, the centroid of a GT2 FS can be computed by calculating the centroid endpoints of its α planes using the Karnik-Mendel (KM) iterative algorithm. However, there lack closed form formulas for the centroid endpoints of the α planes...
We describe the norm of Fourier operator from Lp(T) to lq(ℤ), and from lp(ℤ) to Lq(T) for all p, q ≥ 1, motivated by the problem of finding sharp uncertainty principles expressed in terms of Rényi entropies.
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