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Título : A Primer on Scientific Programming with Python Tipo de documento: documento electrónico Autores: Hans Petter Langtangen ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2012 Otro editor: Imprint: Springer Colección: Texts in Computational Science and Engineering, ISSN 1611-0994 num. 6 Número de páginas: XXXII, 798 p. 79 illus., 30 illus. in color Il.: online resource ISBN/ISSN/DL: 978-3-642-30293-0 Idioma : Inglés (eng) Palabras clave: Mathematics Software engineering Computer programming science mathematics Physics Computational Science and Engineering Programming Techniques Engineering/Programming Operating Systems of Computing Numerical Clasificación: 51 Matemáticas Resumen: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. Nota de contenido: Preface -- Computing with Formulas -- Loops and Lists -- Functions and Branching -- User Input and Error Handling -- Array Computing and Curve Plotting -- Dictionaries and Strings -- Introduction to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus -- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Migrating Python to Compiled Code -- Technical Topics -- Bibliography -- Index En línea: http://dx.doi.org/10.1007/978-3-642-30293-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32988 A Primer on Scientific Programming with Python [documento electrónico] / Hans Petter Langtangen ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2012 . - XXXII, 798 p. 79 illus., 30 illus. in color : online resource. - (Texts in Computational Science and Engineering, ISSN 1611-0994; 6) .
ISBN : 978-3-642-30293-0
Idioma : Inglés (eng)
Palabras clave: Mathematics Software engineering Computer programming science mathematics Physics Computational Science and Engineering Programming Techniques Engineering/Programming Operating Systems of Computing Numerical Clasificación: 51 Matemáticas Resumen: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science. Nota de contenido: Preface -- Computing with Formulas -- Loops and Lists -- Functions and Branching -- User Input and Error Handling -- Array Computing and Curve Plotting -- Dictionaries and Strings -- Introduction to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus -- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Migrating Python to Compiled Code -- Technical Topics -- Bibliography -- Index En línea: http://dx.doi.org/10.1007/978-3-642-30293-0 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=32988 Ejemplares
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Título : A Primer on Scientific Programming with Python Tipo de documento: documento electrónico Autores: Hans Petter Langtangen ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2011 Colección: Texts in Computational Science and Engineering, ISSN 1611-0994 num. 6 Número de páginas: XXX, 706 p. 72 illus., 28 illus. in color Il.: online resource ISBN/ISSN/DL: 978-3-642-18366-9 Idioma : Inglés (eng) Palabras clave: Mathematics Software engineering Computer programming science mathematics Physics Computational Science and Engineering Programming Techniques Engineering/Programming Operating Systems of Computing Numerical Clasificación: 51 Matemáticas Resumen: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science Nota de contenido: Computing with Formulas -- Loops and Lists -- Functions and Branching -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Files, Strings and Dictionaries -- Introduction to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus.- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Technical Topics -- Bibliography -- Index En línea: http://dx.doi.org/10.1007/978-3-642-18366-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33411 A Primer on Scientific Programming with Python [documento electrónico] / Hans Petter Langtangen ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2011 . - XXX, 706 p. 72 illus., 28 illus. in color : online resource. - (Texts in Computational Science and Engineering, ISSN 1611-0994; 6) .
ISBN : 978-3-642-18366-9
Idioma : Inglés (eng)
Palabras clave: Mathematics Software engineering Computer programming science mathematics Physics Computational Science and Engineering Programming Techniques Engineering/Programming Operating Systems of Computing Numerical Clasificación: 51 Matemáticas Resumen: The book serves as a first introduction to computer programming of scientific applications, using the high-level Python language. The exposition is example- and problem-oriented, where the applications are taken from mathematics, numerical calculus, statistics, physics, biology, and finance. The book teaches "Matlab-style" and procedural programming as well as object-oriented programming. High school mathematics is a required background, and it is advantageous to study classical and numerical one-variable calculus in parallel with reading this book. Besides learning how to program computers, the reader will also learn how to solve mathematical problems, arising in various branches of science and engineering, with the aid of numerical methods and programming. By blending programming, mathematics and scientific applications, the book lays a solid foundation for practicing computational science Nota de contenido: Computing with Formulas -- Loops and Lists -- Functions and Branching -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Files, Strings and Dictionaries -- Introduction to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming -- Sequences and Difference Equations -- Introduction to Discrete Calculus.- Introduction to Differential Equations -- A Complete Differential Equation Project -- Programming of Differential Equations -- Debugging -- Technical Topics -- Bibliography -- Index En línea: http://dx.doi.org/10.1007/978-3-642-18366-9 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=33411 Ejemplares
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Título : A Primer on Scientific Programming with Python Tipo de documento: documento electrónico Autores: Hans Petter Langtangen ; SpringerLink (Online service) Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2009 Colección: Texts in Computational Science and Engineering, ISSN 1611-0994 num. 6 Número de páginas: XXVIII, 694 p Il.: online resource ISBN/ISSN/DL: 978-3-642-02475-7 Idioma : Inglés (eng) Palabras clave: Computer science Software engineering programming Mathematics mathematics Physics Science of Computing Computational and Engineering Programming Techniques Engineering/Programming Operating Systems Numerical Clasificación: 51 Matemáticas Resumen: Theaimofthisbookistoteachcomputerprogrammingusingexamples from mathematics and the natural sciences. We have chosen to use the Python programming language because it combines remarkable power with very clean, simple, and compact syntax. Python is easy to learn and very well suited for an introduction to computer programming. Python is also quite similar to Matlab and a good language for doing mathematical computing. It is easy to combine Python with compiled languages, like Fortran, C, and C++, which are widely used languages forscienti?ccomputations.AseamlessintegrationofPythonwithJava is o?ered by a special version of Python called Jython. The examples in this book integrate programming with appli- tions to mathematics, physics, biology, and ?nance. The reader is - pected to have knowledge of basic one-variable calculus as taught in mathematics-intensive programs in high schools. It is certainly an - vantage to take a university calculus course in parallel, preferably c- taining both classical and numerical aspects of calculus. Although not strictly required, a background in high school physics makes many of the examples more meaningful Nota de contenido: Computing with Formulas -- Basic Constructions -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Sequences and Difference Equations -- Files, Strings, and Dictionaries -- to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming En línea: http://dx.doi.org/10.1007/978-3-642-02475-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34071 A Primer on Scientific Programming with Python [documento electrónico] / Hans Petter Langtangen ; SpringerLink (Online service) . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2009 . - XXVIII, 694 p : online resource. - (Texts in Computational Science and Engineering, ISSN 1611-0994; 6) .
ISBN : 978-3-642-02475-7
Idioma : Inglés (eng)
Palabras clave: Computer science Software engineering programming Mathematics mathematics Physics Science of Computing Computational and Engineering Programming Techniques Engineering/Programming Operating Systems Numerical Clasificación: 51 Matemáticas Resumen: Theaimofthisbookistoteachcomputerprogrammingusingexamples from mathematics and the natural sciences. We have chosen to use the Python programming language because it combines remarkable power with very clean, simple, and compact syntax. Python is easy to learn and very well suited for an introduction to computer programming. Python is also quite similar to Matlab and a good language for doing mathematical computing. It is easy to combine Python with compiled languages, like Fortran, C, and C++, which are widely used languages forscienti?ccomputations.AseamlessintegrationofPythonwithJava is o?ered by a special version of Python called Jython. The examples in this book integrate programming with appli- tions to mathematics, physics, biology, and ?nance. The reader is - pected to have knowledge of basic one-variable calculus as taught in mathematics-intensive programs in high schools. It is certainly an - vantage to take a university calculus course in parallel, preferably c- taining both classical and numerical aspects of calculus. Although not strictly required, a background in high school physics makes many of the examples more meaningful Nota de contenido: Computing with Formulas -- Basic Constructions -- Input Data and Error Handling -- Array Computing and Curve Plotting -- Sequences and Difference Equations -- Files, Strings, and Dictionaries -- to Classes -- Random Numbers and Simple Games -- Object-Oriented Programming En línea: http://dx.doi.org/10.1007/978-3-642-02475-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34071 Ejemplares
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Título : Production Planning by Mixed Integer Programming Tipo de documento: documento electrónico Autores: Yves Pochet ; SpringerLink (Online service) ; Laurence A. Wolsey Editorial: New York, NY : Springer New York Fecha de publicación: 2006 Colección: Springer Series in Operations Research and Financial Engineering, ISSN 1431-8598 Número de páginas: XXIV, 500 p Il.: online resource ISBN/ISSN/DL: 978-0-387-33477-6 Idioma : Inglés (eng) Palabras clave: Business Production management Operations research Decision making Software engineering Mathematical models Management science Industrial and Modeling Mathematics Engineering/Programming Operating Systems Research, Science Engineering Operation Research/Decision Theory Clasificación: 51 Matemáticas Resumen: This textbook provides a comprehensive modeling, reformulation and optimization approach for solving production planning and related supply chain planning problems, covering topics from a basic introduction to planning systems, mixed integer programming (MIP) models and algorithms through the advanced description of mathematical results in polyhedral combinatorics required to solve these problems. This book addresses the solution of real life or industrial production planning problems (involving complex production structures with multiple production stages) using a MIP modeling and reformulation approach. It is based on close to twenty years of research in which the authors have played a significant role. One of the goals of this book is to allow non-expert readers, students in business, engineering, applied mathematics and computer science to solve such problems using standard modeling tools and MIP software. To achieve this the book provides a unique collection of reformulation results, integrating them into a comprehensive modeling and reformulation approach, as well as an easy to use problem-solving library. Moreover this approach is demonstrated through a series of real life case studies, exercises and detailed illustrations. Graduate students and researchers in operations research, management, science and applied mathematics wishing to gain a deeper understanding of the formulations and mathematics underlying this approach will find this book useful because of its detailed treatment of the polyhedral structure of the basic lot-sizing problems and simple mixed integer sets that arise in the decomposition of more complicated problems. This book will allow the reader to improve formulations of non-standard MIP models and produce state-of-the-art models and algorithms Nota de contenido: Production Planning and MIP -- The Modeling and Optimization Approach -- Production Planning Models and Systems -- Mixed Integer Programming Algorithms -- Classification and Reformulation -- Reformulations in Practice -- Basic Polyhedral Combinatorics for Production Planning and MIP -- Mixed Integer Programming Algorithms and Decomposition Approaches -- Single-Item Uncapacitated Lot-Sizing -- Basic MIP and Fixed Cost Flow Models -- Single-Item Lot-Sizing -- Lot-Sizing with Capacities -- Backlogging and Start-Ups -- Single-Item Variants -- Multi-Item Lot-Sizing -- Multi-Item Single-Level Problems -- Multi-Level Lot-Sizing Problems -- Problem Solving -- Test Problems En línea: http://dx.doi.org/10.1007/0-387-33477-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34804 Production Planning by Mixed Integer Programming [documento electrónico] / Yves Pochet ; SpringerLink (Online service) ; Laurence A. Wolsey . - New York, NY : Springer New York, 2006 . - XXIV, 500 p : online resource. - (Springer Series in Operations Research and Financial Engineering, ISSN 1431-8598) .
ISBN : 978-0-387-33477-6
Idioma : Inglés (eng)
Palabras clave: Business Production management Operations research Decision making Software engineering Mathematical models Management science Industrial and Modeling Mathematics Engineering/Programming Operating Systems Research, Science Engineering Operation Research/Decision Theory Clasificación: 51 Matemáticas Resumen: This textbook provides a comprehensive modeling, reformulation and optimization approach for solving production planning and related supply chain planning problems, covering topics from a basic introduction to planning systems, mixed integer programming (MIP) models and algorithms through the advanced description of mathematical results in polyhedral combinatorics required to solve these problems. This book addresses the solution of real life or industrial production planning problems (involving complex production structures with multiple production stages) using a MIP modeling and reformulation approach. It is based on close to twenty years of research in which the authors have played a significant role. One of the goals of this book is to allow non-expert readers, students in business, engineering, applied mathematics and computer science to solve such problems using standard modeling tools and MIP software. To achieve this the book provides a unique collection of reformulation results, integrating them into a comprehensive modeling and reformulation approach, as well as an easy to use problem-solving library. Moreover this approach is demonstrated through a series of real life case studies, exercises and detailed illustrations. Graduate students and researchers in operations research, management, science and applied mathematics wishing to gain a deeper understanding of the formulations and mathematics underlying this approach will find this book useful because of its detailed treatment of the polyhedral structure of the basic lot-sizing problems and simple mixed integer sets that arise in the decomposition of more complicated problems. This book will allow the reader to improve formulations of non-standard MIP models and produce state-of-the-art models and algorithms Nota de contenido: Production Planning and MIP -- The Modeling and Optimization Approach -- Production Planning Models and Systems -- Mixed Integer Programming Algorithms -- Classification and Reformulation -- Reformulations in Practice -- Basic Polyhedral Combinatorics for Production Planning and MIP -- Mixed Integer Programming Algorithms and Decomposition Approaches -- Single-Item Uncapacitated Lot-Sizing -- Basic MIP and Fixed Cost Flow Models -- Single-Item Lot-Sizing -- Lot-Sizing with Capacities -- Backlogging and Start-Ups -- Single-Item Variants -- Multi-Item Lot-Sizing -- Multi-Item Single-Level Problems -- Multi-Level Lot-Sizing Problems -- Problem Solving -- Test Problems En línea: http://dx.doi.org/10.1007/0-387-33477-7 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34804 Ejemplares
Signatura Medio Ubicación Sub-localización Sección Estado ningún ejemplar Mathematics and Computation, a Contemporary View / SpringerLink (Online service) ; Hans Munthe Kaas ; Brynjulf Owren (2008)
Título : Mathematics and Computation, a Contemporary View : The Abel Symposium 2006 Proceedings of the Third Abel Symposium, Alesund, Norway, May 25–27, 2006 Tipo de documento: documento electrónico Autores: SpringerLink (Online service) ; Hans Munthe Kaas ; Brynjulf Owren Editorial: Berlin, Heidelberg : Springer Berlin Heidelberg Fecha de publicación: 2008 Colección: Abel Symposia, ISSN 2193-2808 num. 3 Número de páginas: XIV, 127 p Il.: online resource ISBN/ISSN/DL: 978-3-540-68850-1 Idioma : Inglés (eng) Palabras clave: Mathematics Software engineering Computers Computer science mathematics Numerical analysis Analysis Engineering/Programming and Operating Systems Theory of Computation Computational Computing Clasificación: 51 Matemáticas Resumen: The 2006 Abel symposium is focusing on contemporary research involving interaction between computer science, computational science and mathematics. In recent years, computation has been affecting pure mathematics in fundamental ways. Conversely, ideas and methods of pure mathematics are becoming increasingly important within computational and applied mathematics. At the core of computer science is the study of computability and complexity for discrete mathematical structures. Studying the foundations of computational mathematics raises similar questions concerning continuous mathematical structures. There are several reasons for these developments. The exponential growth of computing power is bringing computational methods into ever new application areas. Equally important is the advance of software and programming languages, which to an increasing degree allows the representation of abstract mathematical structures in program code. Symbolic computing is bringing algorithms from mathematical analysis into the hands of pure and applied mathematicians, and the combination of symbolic and numerical techniques is becoming increasingly important both in computational science and in areas of pure mathematics. We are witnessing a development where a focus on computability, computing and algorithms is contributing towards a unification of areas of computer science, applied and pure mathematics. The 2006 Abel symposium brought together some of the leading international researchers working in these areas, presented a snapshot of current state of the art, and raised questions about future research directions Nota de contenido: Geometric Methods in Engineering Applications -- Boundary Integral Equations for the Laplace-Beltrami Operator -- Numerical Study of Nearly Singular Solutions of the 3-D Incompressible Euler Equations -- Energy-Preserving and Stable Approximations for the Two-Dimensional Shallow Water Equations -- A Conjecture about Molecular Dynamics -- The Dynamics of Transition to Turbulence in Plane Couette Flow En línea: http://dx.doi.org/10.1007/978-3-540-68850-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34319 Mathematics and Computation, a Contemporary View : The Abel Symposium 2006 Proceedings of the Third Abel Symposium, Alesund, Norway, May 25–27, 2006 [documento electrónico] / SpringerLink (Online service) ; Hans Munthe Kaas ; Brynjulf Owren . - Berlin, Heidelberg : Springer Berlin Heidelberg, 2008 . - XIV, 127 p : online resource. - (Abel Symposia, ISSN 2193-2808; 3) .
ISBN : 978-3-540-68850-1
Idioma : Inglés (eng)
Palabras clave: Mathematics Software engineering Computers Computer science mathematics Numerical analysis Analysis Engineering/Programming and Operating Systems Theory of Computation Computational Computing Clasificación: 51 Matemáticas Resumen: The 2006 Abel symposium is focusing on contemporary research involving interaction between computer science, computational science and mathematics. In recent years, computation has been affecting pure mathematics in fundamental ways. Conversely, ideas and methods of pure mathematics are becoming increasingly important within computational and applied mathematics. At the core of computer science is the study of computability and complexity for discrete mathematical structures. Studying the foundations of computational mathematics raises similar questions concerning continuous mathematical structures. There are several reasons for these developments. The exponential growth of computing power is bringing computational methods into ever new application areas. Equally important is the advance of software and programming languages, which to an increasing degree allows the representation of abstract mathematical structures in program code. Symbolic computing is bringing algorithms from mathematical analysis into the hands of pure and applied mathematicians, and the combination of symbolic and numerical techniques is becoming increasingly important both in computational science and in areas of pure mathematics. We are witnessing a development where a focus on computability, computing and algorithms is contributing towards a unification of areas of computer science, applied and pure mathematics. The 2006 Abel symposium brought together some of the leading international researchers working in these areas, presented a snapshot of current state of the art, and raised questions about future research directions Nota de contenido: Geometric Methods in Engineering Applications -- Boundary Integral Equations for the Laplace-Beltrami Operator -- Numerical Study of Nearly Singular Solutions of the 3-D Incompressible Euler Equations -- Energy-Preserving and Stable Approximations for the Two-Dimensional Shallow Water Equations -- A Conjecture about Molecular Dynamics -- The Dynamics of Transition to Turbulence in Plane Couette Flow En línea: http://dx.doi.org/10.1007/978-3-540-68850-1 Link: https://biblioteca.cunef.edu/gestion/catalogo/index.php?lvl=notice_display&id=34319 Ejemplares
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