Mathematical modelling : a tool for problem solving in engineering, physical, biological, and social sciences

Bibliographic Information

Mathematical modelling : a tool for problem solving in engineering, physical, biological, and social sciences

D.N.P. Murthy and N.W. Page and E.Y. Rodin

(International series in modern applied mathematics and computer science, v. 20)

Pergamon Press, 1990

1st ed

Available at  / 28 libraries

Search this Book/Journal

Note

Includes bibliographical references and index

Description and Table of Contents

Description

The critical step in the use of mathematics for solving real world problems is the building of a suitable mathematical model. This book advocates a novel approach to the teaching of the building process for mathematical models, with emphasis on the art as well as the science aspects. Using a case study approach, the book teaches the mathematical modelling process in a comprehensive framework, presenting an overview of the concepts and techniques needed for modelling. The book is structured in three parts; the first dealing with the science aspect; the second dealing with the art aspects; and the third combining self learning exercises for the student and supplementary resource material for the instructor.

Table of Contents

Section headings and selected contents: Part I: Methodology and Tools: Role of Mathematics in Problem Solving. The nature of mathematical modelling. Problem Definition: The Starting Point. Case study E: World population. System Characterization. Static vs dynamic. Mathematical Modelling. Analog and simulation models. Mathematical Formulations - I. Partial differential equation (P.D.E) formulations. Analysis of Mathematical Formulations - I. Types of computers and the nature of computed solutions. Mathematical Formulations - II. Discrete state/continuous time formulations. Analysis of Mathematical Formulations - II. Analysis of stochastic processes. Simulation. Digital simulation methodology. Parameter Estimation. Stochastic model parameter estimation. Design of Experiment. Response surface design. Validation. Validation of stochastic models. Pitfalls in Modelling. Part II: Case Studies: Dynamics of Malaria Spread. System characterization. Designing a Pneumatic Pump. Forecasting Airline Passenger Growth. Part III: Supplementary Material: Modelling Exercises. Reference Material. Index.

by "Nielsen BookData"

Related Books: 1-1 of 1

Details

  • NCID
    BA10361359
  • ISBN
    • 0080372449
  • LCCN
    89016246
  • Country Code
    uk
  • Title Language Code
    eng
  • Text Language Code
    eng
  • Place of Publication
    Oxford ; New York
  • Pages/Volumes
    xvi, 339 p.
  • Size
    24 cm
  • Classification
  • Subject Headings
  • Parent Bibliography ID
Page Top