The Method of almost convergence with operator of the form fractional order and applications

The purpose of this paper is twofold. First, basic concepts such as Gamma function, almost convergence, fractional order difference operator and sequence spaces are given as a survey character. Thus, the current knowledge about those concepts are presented. Second, we construct the almost convergent spaces with fractional order difference operator and compute dual spaces which are help us in the characterization of matrix mappings. After we characterize to the matrix transformations, we give some examples.Comment: 20 pages, 4 table

Correlation Coefficients of Fermatean Fuzzy Sets with a Medical Application

The FFS is an influential extension of the available IFS and PFS, whose benefit is to better exhaustively characterize ambiguous information. For FFSs, the correlation between them is usually evaluated by the correlation coefficient. To reflect the perspective of professionals, in this paper, a new correlation coefficient of FFSs is proposed and investigated. The correlation coefficient is very important and frequently used in every field from engineering to economics, from technology to science. In this paper, we propose a new correlation coefficient and weighted correlation coefficient formularization to evaluate the affair between two FFSs. A numerical example of diagnosis has been gotten to represent the efficiency of the presented approximation. Outcomes calculated by the presented approximation are compared with the available indices

HILBERT MATRIX AND DIFFERENCE OPERATOR OF ORDER m

In this paper, some applications of the Hilbert matrix in image processing and cryptology are mentioned and an algorithm related to the Hilbert view of a digital image is given. New matrix domains are constructed and some of their properties are investigated. Furthermore, dual spaces of new matrix domains are computed and matrix transformations are characterized. Finally, examples of transformations of new spaces are given

On Infinite Bernoulli Matrices

In this work, we study some properties of infinite Bernoulli matrices. Further, we investigate relations between infinite Bernoulli matrices and some infinite matrices such as Fibonacci, Pascal and special matrices

ON THE TAYLOR SEQUENCE SPACES OF NONABSOLUTE TYPE WHICH INCLUDE THE SPACES c(0) AND c

Let T(r) denotes the Taylor method of order r such that r is an element of C/{0}. In this paper, we introduce Taylor sequence spaces t(0)(r) and t(c)(r) consisting of all sequences whose T(r)-transforms are in the spaces c(0) and c. We investigate some properties and compute alpha-, beta- and gamma-duals of these spaces. Afterwards, we characterize of some matrix classes of Taylor sequence spaces t(0)(r) and t(c)(r) and give Steinhaus type theorems

The Hahn Sequence Space Defined by the Cesaro Mean

The BK-space of all sequences is given as x = (x(k)) such that Sigma(infinity)(k=1)k vertical bar x(k) - x(k+1)vertical bar converges and x(k) is a null sequence which is called the Hahn sequence space and is denoted by h. Hahn (1922) defined the h space and gave some general properties. G. Goes and S. Goes (1970) studied the functional analytic properties of this space. The study of Hahn sequence space was initiated by Chandrasekhara Rao (1990) with certain specific purpose in the Banach space theory. In this paper, the matrix domain of the Hahn sequence space determined by the Cesaro mean first order, denoted by C, is obtained, and some inclusion relations and some topological properties of this space are investigated. Also dual spaces of this space are computed and, matrix transformations are characterized

Fibonacci statistical convergence on intuitionistic fuzzy normed spaces

In this paper, we study the concept of Fibonacci statistical convergence on intuitionisitic fuzzy normed space. We define the Fibonacci statistically Cauchy sequences with respect to an intuitionisitic fuzzy normed space and introduce the Fibonacci statistical completenes with respect to an intuitionisitic fuzzy normed space

Comparison of Medical Decision-Making with Intuitionistic Fuzzy Parametrized Fuzzy Soft Set and Riesz Summability

In the present study, for the medical decision-making problem, the proposed techniques related to the intuitionistic fuzzy parametrized soft sets and Riesz mean methods were used. The results of the given methods were compared. The values obtained from the methods were ordered and the success of the measurement techniques of the methods were evaluated. The real dataset which is called Cleveland heart disease dataset was applied in this problem

Comparison of artificial neural network and logistic regression model for factors affecting birth weight

The aim of this work compares the ANN and logistic regression analysis to determine the factors affecting birth weight. This study included 223 newborn babies. The records of babies born between January 2017 and December 2017 were used. The data were obtained from Beykoz district of Istanbul. ANN and logistic regression analysis of the method obtained based on these records were evaluated. Logistic regression revealed the items GB, MA, GA, NH, BMI, MPPW, MWGP, MsAU, MsCU, MsE as significant factors for BW.The area under the receiver operating characteristic (AuROC) curve 0.941 (SD = 0.0012) for ANN and 0.909 (SD = 0.019) for Logistic Regression model.The ANNs may be trained with data acquired in various contexts and can consider local expertise, differences, and other variables with uncertain effects on outcome. Although the ANN value is greater than the LR value, these results are very close to each other.This shows us that in terms of their classification ability, these two methods are approximately equal to each other.The results we have seen in our study show that in the medical diagnosis, neither model can change the other. Both models can be used as a complement to help with decision-making. Both models have the potential to help physicians with respect to understanding BW risk factors, risk estimation