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  Browse All Reviews > Mathematics Of Computing (G) > Numerical Analysis (G.1) > General (G.1.0) > Numerical Algorithms (G.1.0...)  
 
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  1-10 of 194 Reviews about "Numerical Algorithms (G.1.0...)": Date Reviewed
  Metaheuristics
Siarry P.,  Springer International Publishing, New York, NY, 2016. 489 pp. Type: Book (978-3-319454-01-6)

Practical real-life problems that occur in the design of electrical or mechanical systems, image processing, transportation, manufacturing, operations research, and so on can often be expressed as optimization problems. Many hard optimization prob...

Jan 30 2018
  A linear algorithm for a perfect matching in polyomino graphs
Lin Y., Zhang F.  Theoretical Computer Science 67582-88, 2017. Type: Article

Perfect matching in a graph is a set of edges where any pair does not share a common vertex and every vertex of the graph is the endpoint of an edge from that set. From the paper’s introduction: “A polyomino graph is a connected finite...

Aug 10 2017
  Wonderful solutions and habitual domains for challenging problems in changeable spaces: from theoretical framework to applications
Larbani M., Yu P.,  Springer International Publishing, New York, NY, 2016. 275 pp. Type: Book

The lengthy, lilting title forecasts the creativity and unconventionality of a book that seeks to revolutionize decision making by expanding the solution space to take into account that some quantitative factors change as the problem is addressed ...

May 26 2017
  Topics in numerical partial differential equations and scientific computing
Brenner S.,  Springer International Publishing, New York, NY, 2016. 176 pp. Type: Book (978-1-493963-98-0)

The Association for Women in Mathematics (AWM) was founded in 1971, to encourage women to have careers in mathematical sciences. They held a research collaboration workshop in August 2014, hosted by the Institute for Mathematics and its Applicatio...

Feb 24 2017
  Numerical methods and modelling for engineering
Khoury R., Harder D.,  Springer International Publishing, New York, NY, 2016. 332 pp. Type: Book (978-3-319211-75-6)

I always appreciated numerical methods courses, possibly because I found the field a simpler and more versatile alternative to learning the analytic solutions across many application domains. Although this book is intended as a textbook for studen...

Feb 23 2017
  IsoGeometric analysis: a new paradigm in the numerical approximation of PDEs
Buffa A., Sangalli G.,  Springer International Publishing, New York, NY, 2016. 193 pp. Type: Book (978-3-319423-08-1)

For their daily work, computational engineers in many technical disciplines rely heavily on the use of finite element software systems. However, certain features of the traditional mathematical approaches on which these systems are based impose li...

Feb 22 2017
  A new faster algorithm for factoring skew polynomials over finite fields
Caruso X., Le Borgne J.  Journal of Symbolic Computation 79, Part 2, 411-443, 2017. Type: Article

Let k be a finite field of characteristic p and size pqr, and let σ be an automorphism of k of order r. The ring of skew polynomials
Jan 13 2017
  Using regression makes extraction of shared variation in multiple datasets easy
Korpela J., Henelius A., Ahonen L., Klami A., Puolamäki K.  Data Mining and Knowledge Discovery 30(5): 1112-1133, 2016. Type: Article

This interesting paper presents an application that could be of value to individuals working in data analysis of sets, trying to find commonalities among what appears to be unrelated data. The idea behind the derivation of shared variation is mean...

Nov 23 2016
  Optimal error estimates of linearized Crank-Nicolson Galerkin method for Landau-Lifshitz equation
An R.  Journal of Scientific Computing 69(1): 1-27, 2016. Type: Article

The Landau–Lifshitz equation is a well-known mathematical model for describing the evolution of magnetization in ferromagnets. It is a partial differential equation that, due to its nonlinear structure, poses a number of challenges when one tries ...

Nov 23 2016
  Real quantifier elimination for the synthesis of optimal numerical algorithms (case study: square root computation)
Eraşcu M., Hong H.  Journal of Symbolic Computation 75(C): 110-126, 2016. Type: Article

If we know that lies in [L,U], can we produce a better bounding interval? The obvious answer is the Secant-Newton map, replacing [L,U
Jul 25 2016
 
 
 
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