Class Central is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

XuetangX

Scientific Computing and Mathematical Modeling

Colorado State University via XuetangX

Overview

"Scientific Computing and Mathematical Modeling" is a basic course for all science and engineering majors in Central South University, with 64 credit hours and 4 credits. This course is based on mathematical modeling ideas and methods, organically integrated into the theory and methods of scientific computing. It is a new course integrating scientific computing methods, modern mathematics, computer technology and practical problem solving. It adopts research teaching and exploration. The teaching model of combination of type learning mainly teaches mathematical modeling ideas and scientific calculation methods. In the teaching process, taking practical problems as the background, adopting case teaching methods, infiltrating mathematical modeling ideas, introducing mathematical modeling steps and methods, establishing mathematical models to describe practical problems, and introducing basic knowledge of scientific computing with the solution of the models General methods; main contents include: basic concepts and interrelationships of mathematical modeling and scientific computing methods, error analysis theory, function interpolation and fitting methods, numerical integration methods, equation solving numerical methods, AHP modeling, comprehensive evaluation, Time series analysis, statistical analysis and prediction methods, mathematical modeling case analysis, etc.

The "Scientific Computing and Mathematical Modeling" curriculum emphasizes practical application, puts students first, highlights experimental and practical teaching links, realizes the combination of extracurricular and extracurricular, and attaches importance to the cultivation of students' independent learning ability, innovative ability and extracurricular practical ability, content The organization fully considers the students 'mathematics foundation, and at the same time deepens and expands students' mathematical knowledge, which can be applied to the requirements of various levels of different majors.

Teaching objectives

One of the important goals of the course teaching is to improve students' ability to apply mathematical knowledge to solve practical problems, comprehensively train students to use mathematical tools to build mathematical models, and apply scientific calculation methods to solve practical problems. The scientific computing ability, mathematical modeling ability and scientific research paper writing ability, cultivate the ability to engage in modern scientific research activities and related qualities.





Syllabus

  • Chapter 1 Mathematical Modeling and Error Analysis-Introduction
    • 1.1-Mathematics and Scientific Computing
    • 1.2-Mathematical Modeling and Its Significance
    • 1.3-Numerical Methods and Evaluation of Algorithms
    • 1.4-Types and Sources of Errors
    • 1.5-Absolute Error and Relative Error
    • 1.6-Error Propagation and Algorithm Stability Analysis
  • Chapter 2 Forecast Model of Urban Water Supply-Interpolation and Fitting Algorithm
    • 2.1-The problem of urban water supply forecast and the concept of interpolation
    • 2.2-Lagrange Method for Finding Interpolating Polynomials
    • 2.3-Newton's Method for Interpolating Polynomials
    • 2.4-Error Analysis of Interpolation Polynomial
    • 2.5-Improved Algorithm for Interpolation Polynomial
    • 2.6-Fitting Algorithm for Function Approximation
    • 2.7-Simple Method and Numerical Differentiation of Urban Water Supply Forecast
  • Chapter 3 Xiangjiang Flow Estimation Model-Numerical Integration Method
    • 3.1-Construction of Numerical Integration Formula and Algebraic Precision
    • 3.2-Newton-Cotes Integration Method
    • 3.3-Romberg Algorithm
    • 3.4-Gauss Integration Method and Node Position Optimization
  • Chapter 4 Issues of Pension Insurance-Numerical Solution of Nonlinear Equations
    • 4.1-The Problem of Pension Insurance and The Search for roots
    • 4.2-Iterative Solution of Nonlinear Equations
    • 4.3-Newton Iteration Method
    • 4.4-String Cut Method and Parabolic Method
  • Chapter 5 Asteroid Orbit Equation Calculation Problem-Direct Method for Solving Linear Equations
    • 5.1-Asteroid orbit calculation problem and line Overview of Direct Solution of Sexual Equations
    • 5.2-Gauss elimination method
    • 5.3-Matrix triangulation and Gauss elimination
    • 5.4-Gauss Principal Elimination
    • 5.5-Direct triangulation
    • 5.6-Square root method
    • 5.7-Chasing method
  • Chapter 6 The Regression Problem-Iterative Method for Solving Linear Equations
    • 6.1-Overview of iterative solutions for linear equations
    • 6.2-Convergence of the iterative method of linear equations
    • 6.3-Construction of iteration method and basic iteration method
    • 6.4-Over-relaxation iteration method
  • Chapter 7 Infectious Disease Model-Introduction to The Numerical Solution of Ordinary Differential Equations
    • 7.1-Differential equation model and infectious disease model of practical
    • 7.2-Simple numerical methods and basic concepts
    • 7.3-Linear Multi-step Method
    • 7.4-Runge-Kutte method
    • 7.5-The problem of initial values of equations and higher-order equations
    • 7.6-Numerical solution of ordinary differential equation boundary value problem
  • Chapter 8 Analytic Hierarchy Process(AHP)
    • 8.1-Overview of decision evaluation and AHP
    • 8.2-Basic steps of AHP
    • 8.3-Wide application of AHP
    • 8.4-Some problems of AHP
  • Chapter 9 Comprehensive Evaluation of Yangtze River Water Quality-Comprehensive Evaluation Method and Its Application
    • 9.1-Comprehensive evaluation of the water quality of the Yangtze River
    • 9.2-Introduction to comprehensive evaluation methods
    • 9.3-Water quality comprehensive evaluation model for the Yangtze River
    • 9.4-Comprehensive evaluation result of the water quality & determination of pollution source of the Yangtze River
  • Chapter 10 Statistical Forecast Methods and Forecast Model
    • 10.1-Statistical forecast
    • 10.2-Trend extrapolation forecast
    • 10.3-Deterministic factor analysis of time series
    • 10.4-Regression forecast method
    • 10.5-Multiple linear regression model
  • Exam

    Taught by

    Zhoushun Zheng

    Reviews

    Start your review of Scientific Computing and Mathematical Modeling

    Never Stop Learning.

    Get personalized course recommendations, track subjects and courses with reminders, and more.

    Someone learning on their laptop while sitting on the floor.