力学系に適した数値データ(CD-ROM付)<br>Numerical Data Fitting in Dynamical Systems : A Practical Introduction with Applications and Software (Applied Optimization)

個数:

力学系に適した数値データ(CD-ROM付)
Numerical Data Fitting in Dynamical Systems : A Practical Introduction with Applications and Software (Applied Optimization)

  • 在庫がございません。海外の書籍取次会社を通じて出版社等からお取り寄せいたします。
    通常6~9週間ほどで発送の見込みですが、商品によってはさらに時間がかかることもございます。
    重要ご説明事項
    1. 納期遅延や、ご入手不能となる場合がございます。
    2. 複数冊ご注文の場合、分割発送となる場合がございます。
    3. 美品のご指定は承りかねます。
  • 【入荷遅延について】
    世界情勢の影響により、海外からお取り寄せとなる洋書・洋古書の入荷が、表示している標準的な納期よりも遅延する場合がございます。
    おそれいりますが、あらかじめご了承くださいますようお願い申し上げます。
  • ◆画像の表紙や帯等は実物とは異なる場合があります。
  • ◆ウェブストアでの洋書販売価格は、弊社店舗等での販売価格とは異なります。
    また、洋書販売価格は、ご注文確定時点での日本円価格となります。
    ご注文確定後に、同じ洋書の販売価格が変動しても、それは反映されません。
  • 製本 Hardcover:ハードカバー版/ページ数 392 p.
  • 言語 ENG
  • 商品コード 9781402010798
  • DDC分類 004.21

Full Description

Real life phenomena in engineering, natural, or medical sciences are often described by a mathematical model with the goal to analyze numerically the behaviour of the system. Advantages of mathematical models are their cheap availability, the possibility of studying extreme situations that cannot be handled by experiments, or of simulating real systems during the design phase before constructing a first prototype. Moreover, they serve to verify decisions, to avoid expensive and time consuming experimental tests, to analyze, understand, and explain the behaviour of systems, or to optimize design and production. As soon as a mathematical model contains differential dependencies from an additional parameter, typically the time, we call it a dynamical model. There are two key questions always arising in a practical environment: 1 Is the mathematical model correct? 2 How can I quantify model parameters that cannot be measured directly? In principle, both questions are easily answered as soon as some experimental data are available. The idea is to compare measured data with predicted model function values and to minimize the differences over the whole parameter space. We have to reject a model if we are unable to find a reasonably accurate fit. To summarize, parameter estimation or data fitting, respectively, is extremely important in all practical situations, where a mathematical model and corresponding experimental data are available to describe the behaviour of a dynamical system.

Contents

1 Introduction.- 2 Mathematical Foundations.- 3 Data Fitting Models.- 4 Numerical Experiments.- 5 Case Studies.- Appendix A: Software Installation.- 1 Hardware and Software Requirements.- 2 System Setup.- 3 Packing List.- Appendix B: Test Examples.- 1 Explicit Model Functions.- 2 Laplace Transforms.- 3 Steady State Equations.- 4 Ordinary Differential Equations.- 5 Differential Algebraic Equations.- 6 Partial Differential Equations.- 7 Partial Differential Algebraic Equations.- Appendix C: The PCOMP Language.- Appendix D: Generation of Fortran Code.- 1 Model Equations.- 1.1 Input of Explicit Model Functions.- 1.2 Input of Laplace Transformations.- 1.3 Input of Systems of Steady State Equations.- 1.4 Input of Ordinary Differential Equations.- 1.5 Input of Differential Algebraic Equations.- 1.6 Input of Time-Dependent Partial Differential Equations.- 1.7 Input of Partial Differential Algebraic Equations.- 2 Execution of Generated Code.- References.