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a comparative evaluation of matlab, octave, freemat - here
a comparative evaluation of matlab, octave, freemat - here

... Scilab, and provide information on which package is most compatible to Matlab users. Section 1.3 provides more detailed descriptions of these packages. To evaluate GNU Octave, FreeMat, and Scilab, a comparative approach is used based on a Matlab user’s perspective. To achieve this task, we perform s ...
A Comparative Analysis of Different Categorical Data Clustering
A Comparative Analysis of Different Categorical Data Clustering

... emerged over earlier periods. Conversely it is known that there is no single clustering method is capable of providing accurate and appropriate cluster results [14]. Since by applying a clustering algorithm to the data set it works on the basis of the internal criteria i.e. similarity or dissimilari ...
A Review of Recent Developments in Solving ODES
A Review of Recent Developments in Solving ODES

... Although many of the current methods for solving ODES were developed around the turn of the century, the past 15 years or so has been a period of intensive research. The emphasis of this survey is on the methods and techniques used in software for solving ODES. ODES can be classified as stiff or non ...
08_524 - Bangladesh Mathematical Society
08_524 - Bangladesh Mathematical Society

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Preconditioning of Markov Chain Monte Carlo Simulations Using
Preconditioning of Markov Chain Monte Carlo Simulations Using

... pre-computed multiscale basis functions and solve the saturation on the fine grid. This provides an accurate approximation for the production data [13, 14, 1]. Since one can re-use the basis functions from the first stage, the resulting method is very efficient. We would like to note that upscaled m ...
Exact Solution of Time History Response for Dynamic
Exact Solution of Time History Response for Dynamic

... with operation count of approximately the cube of the number of retained real modes and is not exact because of the linear approximations. Alternatively, Picard iteration can be used to solve the pseudo-uncoupled equations, see [11] and others. An alternative is to express the dynamic equations in s ...
Numerical Solution of Differential Equations with Orthogonal
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Line search methods, Wolfe`s conditions

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... A local variable: a variable defined inside a method. Scope: the part of the program where the variable can be referenced. The scope of a local variable starts from its declaration and continues to the end of the block that contains the variable. A local variable must be declared before it can be us ...
Numerical Methods for the solution of Hyperbolic
Numerical Methods for the solution of Hyperbolic

... to conservation laws, that is time-dependent systems of partial differential equations (PDEs), usually hyperbolic and nonlinear, with a particularly simple structure. Fluid and gas dynamics, relativity theory, quantum mechanics, aerodynamics, meteorology, astrophysics - this is just a partial list o ...
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Section 5 slides - Emory Math/CS Department
Section 5 slides - Emory Math/CS Department

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a new approach to solve fuzzy non-linear equations using fixed
a new approach to solve fuzzy non-linear equations using fixed

... solution of the fuzzy non-linear equation is obtained with the help of the proposed algorithm and its graphical representation has also been shown as well. Some related definitions and some operations on linear fuzzy real numbers [3, 5-10], which will be used later to obtain a solution of fuzzy nonl ...
R-97_ChenHB.pdf
R-97_ChenHB.pdf

... FEMs are not applicable, residue-based and recovery-based error estimation technology in FEM should be applied to meshless method selectively while characters of meshless methods should also be considered. (1) For the EFGM, investigations on error estimations are furnished more than other meshless ...
Licentiate Thesis
Licentiate Thesis

... discretization error coming from the numerical methods; assuming ergodicity, statistical error coming from using a finite time; and modeling error coming from approximations related to the molecular dynamics. In Paper I, we address the modeling error. The aim is to determine quantitative error estim ...
Chebyshev Expansions - Society for Industrial and Applied
Chebyshev Expansions - Society for Industrial and Applied

... For the case of a single interpolation node x0 which is repeated n times, the corresponding interpolating polynomial is just the Taylor polynomial of degree n at x0 . It is very common that successive derivatives of special functions are known at a certain point x = x0 (Taylor’s theorem, (2.1)), but ...
Adomian Method for Second-order Fuzzy Differential Equation
Adomian Method for Second-order Fuzzy Differential Equation

... HE study of fuzzy differential equation (FDE) forms a suitable setting for mathematical modeling of real world problems in which uncertainties or vagueness pervade. The concept of a fuzzy derivative was defined by Chang and Zadeh in [13]. It was followed up by Dubois and Prade in [14], who used the e ...
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Root-finding algorithm

A root-finding algorithm is a numerical method, or algorithm, for finding a value x such that f(x) = 0, for a given function f. Such an x is called a root of the function f.This article is concerned with finding scalar, real or complex roots, approximated as floating point numbers. Finding integer roots or exact algebraic roots are separate problems, whose algorithms have little in common with those discussed here. (See: Diophantine equation for integer roots)Finding a root of f(x) − g(x) = 0 is the same as solving the equation f(x) = g(x). Here, x is called the unknown in the equation. Conversely, any equation can take the canonical form f(x) = 0, so equation solving is the same thing as computing (or finding) a root of a function.Numerical root-finding methods use iteration, producing a sequence of numbers that hopefully converge towards a limit, which is a root. The first values of this series are initial guesses. Many methods computes subsequent values by evaluating an auxiliary function on the preceding values. The limit is thus a fixed point of the auxiliary function, which is chosen for having the roots of the original equation as fixed points.The behaviour of root-finding algorithms is studied in numerical analysis. Algorithms perform best when they take advantage of known characteristics of the given function. Thus an algorithm to find isolated real roots of a low-degree polynomial in one variable may bear little resemblance to an algorithm for complex roots of a ""black-box"" function which is not even known to be differentiable. Questions include ability to separate close roots, robustness against failures of continuity and differentiability, reliability despite inevitable numerical errors, and rate of convergence.
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