Mathematical study of BLUES function method for KdV Burgers’ and BBM-Burgers’ equations

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Mathematical study of BLUES function method for KdV Burgers’ and BBM-Burgers’ equations

ReferencesShowing 10 of 32 papers
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A fractional Temimi‐Ansari method (FTAM) with convergence analysis for solving physical equations
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Numerical Simulation of Time Fractional BBM-Burger Equation Using Cubic B-Spline Functions
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Exp-function method for nonlinear wave equations
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Exact solitary wave solutions for a generalized KdV–Burgers equation
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A continuum model with traffic interruption probability and electronic throttle opening angle effect under connected vehicle environment
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Approximate explicit solutions of nonlinear BBMB equations by homotopy analysis method and comparison with the exact solution
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  • A Fakhari + 2 more

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Theoretical and experimental analysis of pulse compression capability in non-linear magnetic transmission line
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The generalized fractional Benjamin–Bona–Mahony equation: Analytical and numerical results
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  • Physica D: Nonlinear Phenomena
  • Goksu Oruc + 2 more

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BLUES function method applied to partial differential equations and analytic approximants for interface growth under shear
  • Aug 4, 2021
  • Physical Review Research
  • Jonas Berx + 1 more

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  • 10.1007/s00366-021-01406-7
Characteristics of melting heat transport of blood with time-dependent cross-nanofluid model using Keller–Box and BVP4C method
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We have previously developed a model-based method to compensate for the crosstalk in simultaneous acquisition of Tc-99m stress and Tl-201 rest myocardial perfusion SPECT. The purpose of this study is to evaluate the performance of this method in terms of a defect detection task using a mathematical Channelized Hoteling Observer (CHO) study. In this study we also optimized the iteration number in reconstruction of Tl distributions. A population of male and female NCAT phantoms were used to realistically model variation in patients. Both defect-free and defect-present data of Tc and Tl were simulated using the SimSET/PHG codes and our newly developed and validated angular response function (ARF) method to mimic simultaneous acquisition and separate acquisition. Poisson noise was modeled at clinically realistic levels. The Tl data were reconstructed using filtered backprojection (FBP) and ordered subset expectation maximization (OSEM) algorithms for up to 20 iterations with and without the model-based crosstalk compensation (MBC). CHO methodology and receiver operating characteristic (ROC) analysis were applied to short axis Tl images to obtain ROC curves and area under ROC curves (AUC). The AUC values were compared with those from separately acquired data reconstructed using FBP and OSEM algorithms. The results show that a relatively small number of iteration (/spl sim/3) is optimal for the postreconstruction filtering cutoff frequency of 0.16 pixel/sup -1/ used in this study. Also, the AUC values obtained with the MBC were significantly better than those without crosstalk compensation and those with the FBP reconstruction method applied to the separately acquired data.

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Exact solutions of the Rosenau–Hyman equation, coupled KdV system and Burgers–Huxley equation using modified transformed rational function method
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In this research, we study the exact solutions of the Rosenau–Hyman equation, the coupled KdV system and the Burgers–Huxley equation using modified transformed rational function method. In this paper, the simplest equation is the Bernoulli equation. We are not only obtain the exact solutions of the aforementioned equations and system but also give some geometric descriptions of obtained solutions. All can be illustrated vividly by the given graphs.

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defined for x > 0, u > 0. A saddle point of (1.2) is defined to be a point (x*, u*), x* > Q, u* > 0 such that +(x, u*) < +(x*, u*) _ +(x*, u) for all x _ 0, u ? 0. One of the Kuhn-Tucker results is that a saddle point of(1.2) provides a solution to (1.1). Under cer-eain additional regularity assumptions the equivalence of the saddle point problem and the program (1.1) has been shown [1], [10]. In particular, if the feasible set in (1.1) has an interior point (a nonnegative x such that g(x) < b),3 and if the objective function is concave and the constraint functions are convex, then x* is a solution to (1.1) if and only if there is a nonnegative u* such that (x*, u*) is a saddle point of (1.2). This is the so-called Kuhn-Tucker equivalence theorem of nonlinear programming. In this paper Lagrange multipliers are generalized from the usual constants to (possibly nonlinear) multiplier functions. This leads to the statement of several general equivalence results under quite weak assumptions. From a somewhat different point of view, Everett [4] drops differentiability assumptions and discusses a procedure for solving nonlinear programs in terms of

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