Theory of Approximation and Applications
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Theory of Approximation and Applicationsendaily1Sun, 01 Dec 2019 00:00:00 +0330Sun, 01 Dec 2019 00:00:00 +0330Application of semi-analytic method to compute the moments for solution of logistic model
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The population growth, is increase in the number of individuals in population and it depends on some random environment eﬀects. There are several diﬀerent mathematical models for population growth. These models are suitable tool to predict future population growth. One of these models is logistic model. In this paper, by using Feynman-Kac formula, the Adomian decomposition method is applied to compute the moments for the solution of logistic stochastic diﬀerential equation.Nonlinear Viscosity Algorithm with Perturbation for Nonexpansive Multi-Valued Mappings
http://msj.iau-arak.ac.ir/article_670251.html
In this paper, based on viscosity technique with perturbation, we introduce a new non-linear viscosity algorithm for finding a element of the set of fixed points of nonexpansivemulti-valued mappings in a Hilbert space. We derive a strong convergence theorem for thisnew algorithm under appropriate assumptions. Moreover, in support of our results, somenumerical examples (using Matlab software) are also presented.An approximate method for solving fractional system differential equations
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IIn this research work, we have shown that it is possible to use fuzzy transform method (FTM) for the estimate solution of fractional system differential equations (FSDEs). In numerical methods, in order to estimate a function on a particular interval, only a restricted number of points are employed. However, what makes the F-transform preferable to other methods is that it makes use of all points in this interval. A number of clear and specific examples have been enumerated for the purpose of illustrating the simplicity and efficiency of the suggested method.Neutrosophic-Cubic Analaytic Hierarchy Process with Applications
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In this paper we extend fuzzy analytic hierarchy process into neutrosophic cubic environment. The neutrosophic cubic analytic hierarchy process can be used to manage more complex problems when the decision makers has a number of uncertainty, assigning preferences values to the considered object. We also define the concept of triangular neutrosophic cubic numbers and their operations laws. The advantages of the proposed methodology and the application of neutrosophic cubic analytic hierarchy process in decision making are shown by testing the numerical example in practical life.REMOTAL CENTERS AND CHEBYSHEV CENITERS IN NORMED SPACES
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In this paper, we consider Nearest points" and Farthestpoints" in normed linear spaces. For normed space (X; ∥:∥), the set W subset X,we dene Pg; Fg;Rg where g 2 W. We obtion results about on Pg; Fg;Rg. Wend new results on Chebyshev centers in normed spaces. In nally we deneremotal center in normed spaces.A new method for solving two-dimensional fuzzy Fredholm integral equations of the second kind
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In this work, we introduce a novel method for solving two-dimensional fuzzy Fredholm integral equations&nbsp;of the second kind (2D-FFIE-2). We use new representation of parametric form of fuzzy numbers and convert&nbsp;a two-dimensional fuzzy Fredholm integral equation to system of two-dimensional Fredholm integral equations&nbsp;of the second kind in crisp case. We can use Adomian decomposition method for nding the approximation&nbsp;solution of the each equation, hence obtain an approximation for fuzzy solution of 2D-FFIE-2. We prove the&nbsp;convergence of the method and nally apply the method to some examplesUsing finite difference method for solving linear two-point fuzzy boundary value problems based on extension principle
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In this paper an efficient Algorithm based on Zadeh's extension principle has been investigated to approximate fuzzy solution of two-point fuzzy boundary value problems, with fuzzy boundary values. We use finite difference method in term of the upper bound and lower bound of $r$- level of fuzzy boundary values. The proposed approach gives a linear system with crisp tridiagonal coefficients matrix. This linear system determines $r$-level of fuzzy solution at mesh points. By combining of this solutions, we obtain fuzzy solution of main problem at mesh points, approximately. Its applicabilityis illustrated by someexamplesAn extension of stochastic differential models by using the Grunwald-Letnikov fractional derivative
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Stochastic differential equations (SDEs) have been applied by engineers and economists because it can express the behavior of stochastic processes in compact expressions. In this paper, by using Grunwald-Letnikov fractional derivative, the stochastic differential model is improved. Two numerical examples are presented to show efficiency of the proposed model. A numerical optimization approach based on least square approximation is applied to determine the order of the fractional derivative. Numerical examples show that the proposed model works better than the SDE to model stochastic processes with memory.Best Proximity Points Results for Cone Generalized Semi-Cyclic φ-Contraction Maps
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In this paper, we introduce a cone generalized semi-cyclic&phi;&minus;contraction maps and prove best proximity points theorems for such mapsin cone metric spaces. Also, we study existence and convergence results ofbest proximity points of such maps in normal cone metric spaces. Our resultsgeneralize some results on the topic.The existence and uniqueness of the solution for uncertain functional differential equations
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The uncertain functional differential equations are animportant tool to deal with dynamic systems including thepast states in uncertain environments. The contribution ofthis paper to the uncertain functional differential equationtheory is to provide an existence and uniqueness theoremunder the weak Lipschitz condition and the linear growthcondition.Strong algebrability of C^* algebras
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In this paper, we introduce the concept strong algebrability of certain C^* algebras generated by finite generators. In fact, using Gelfand theorem, we identify the members of the C^* algebra generated by one element, with the continuous functions on its spectrum, and use some recent result for strong algebrability for functions spaces.Moreover, we introduce the new concept unitable elements in unital C^* algebras, and then we express our main result for this kind of elements. In fact, the C^* subalgebra generated by a non unitable element in a C^* algebra is strongly c algebrable.As the last result in this paper, we show 2^c strong algebrability of direct sums of C^* algebras, using non unitable elements of themSkew Cyclic Codes Of Arbitrary Length Over R=Fp[v]/(v^2^k -1)
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In thise paper we study an special type of Cyclic Codes called skew Cyclic codes over the ring R=Fp[v]/(v^2^k-1) where is a prime number. This sets Of codes are the result of module (or ring) structure of the skew polynomial ringR=[x,Q] where v^2^k=1 and Q is an Fp automorphism such that Q(v)=v^2^k-1.We show that when n is even these codes are principal and if n is odd these codeLook like a module and proof some properties.The combinatorial of Artificial Bee Colony algorithm and Bisection method for solving Eigenvalue Problem
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The aim of this paper is to find eigenvalues of square matrix A based on the Artificial Bee Colony algorithm and the Bisection method(BIABC ). At first, we obtain initial interval [a,b] that included all eigenvalues based on Gerschgorin&#039;s theorem, and then by using Artificial Bee Colony algorithm(ABC) at this interval to generate initial value for each eigenvalue. The bisection method improves them until the best values of eigenvalues with arbitrary accuracy will be achieved. This enables us to find eigenvalues with arbitrary accuracy without computing the derivative of the characteristic polynomial of the given matrix. We illustrate the proposed method with Some numerical examples.Poison process with fuzzy parameter
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This paper, introduces the fuzzy poisson process that plays an important role in the fuzzy sets and systems; specially, The spatial Poisson point process features prominently in spatial statistics, stochastic geometry, and continuum percolation theory. This point process is applied in various physical sciences such as a model developed for alpha particles being detected. In recent years, it has been frequently used to model seemingly disordered spatial configurations of certain wireless communication networks. For example, models for cellular or mobile phone networks have been developed where it is assumed the phone network transmitters, known as base stations, are positioned according to a homogeneous Poisson point process.