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Numerical Methods

Numerical Method focuses on computational techniques for solving mathematical problems that cannot be solved analytically. It covers methods for solving equations, interpolation, numerical integration, and differential equations, widely used in scientific and engineering applications.

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TabFlux . Numerical Methods . TU . BIT

Numerical Methods

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Course Title: Numerical Methods

Course No: BIT203

Nature of the Course: Theory + Lab

Semester: 3

Full Marks: 60 + 20 + 20

Pass Marks: 24 + 8 + 8

Credit Hours: 3

Course Description

Course Objectives

Course Contents

1. Solution of Nonlinear Equations
7 hrs
1.1. Errors in Numerical Calculations
  • Sources of Errors
  • Propagation of Errors
  • Review of Taylor's Theorem
1.2. Concept of Non-linear Equations and Solving Methods
  • Trial and Error Method
  • Bisection Method
  • Newton Raphson Method
  • Secant Method
  • Fixed Point Method
  • False Position Method
  • Newton's Method for Calculating Multiple Roots
  • Evaluating Polynomials with Horner's Method
2. Interpolation and Regression
8 hrs
2.1. Interpolation
  • Concept of Interpolation and Extrapolation
  • Lagrange's Interpolation
  • Newton's Interpolation using divided differences
  • Newton's Interpolation using forward differences
  • Newton's Interpolation using backward differences
2.2. Regression
  • Concept of Regression
  • Regression vs. Interpolation
  • Least Squares Methods
  • Linear Regression
  • Non-linear Regression: Exponential and Polynomial
3. Numerical Differentiation and Integration
9 hrs
3.1. Numerical Differentiation
  • Concept of Differentiation
  • Differentiating Continuous Functions (Two-Point and Three Point Formula)
  • Differentiating Tabulated Functions by using Newton's Differences
  • Maxima and minima of Tabulated Functions
3.2. Numerical Integration
  • Concept of Integration
  • Newton-Cote's Quadrature Formulas
  • Trapezoidal rule
  • Multi-Segment Trapezoidal rule
  • Simpson's 1/3 rule
  • Multi-Segment Simpson's 1/3 rule
  • Simpson's 3/8 rule
  • Multi-Segment Simpson's 3/8 rule
4. Solving System of Linear Equations
8 hrs
4.1. Direct Methods
  • Existence of Solutions, Properties of Matrices, Matrix Representation
  • Gaussian Elimination Method, Partial and Complete Pivoting
  • Gauss-Jordan method
  • Inverse of matrix using Gauss-Jordan method
4.2. Matrix factorization and Solving System of Linear Equations by using Do-little and Cholesky's algorithm
4.3. Iterative Solutions of System of Linear Equations
  • Jacobi Iteration Method
  • Gauss-Seidal Method
4.4. Eigen Values and Eigen Vectors Problems, Power Method
5. Solution of Ordinary Differential Equations
8 hrs
5.1. Initial Value Problems
  • Concept of Differential Equations
  • Initial Value Problem
  • Taylor Series Method
  • Euler's Method
  • Heun's Method
  • Runge-Kutta Methods
5.2. Higher Order and Boundary Value Problems
  • Solving System of Ordinary Differential Equations
  • Solution of the Higher Order Equations
  • Boundary Value Problems
  • Shooting Method
6. Solution of Partial Differential Equations
5 hrs
6.1. Concept of Partial Differential Equations
6.2. Classification of PDE
6.3. Deriving Difference Equations
6.4. Laplacian Equation and Poisson's Equation

Laboratory Works

  1. 1.Non-linear equations
  2. 2.System of linear equations
  3. 3.Interpolation and Regression
  4. 4.Numerical integration and differentiation
  5. 5.Solving ordinary and partial differential equations

Text Books

  1. 1.W. Chency and D. Kincaid, "Numerical Mathematics and Computing", 7th Edition, Brooks Cole Publisher
  2. 2.C.F. Gerald and P.O. Wheatley, "Applied Numerical Analysis", 9th Edition, Addison Wesley Publisher

Reference Books

  1. 1.W.H. Press, B.P. Flannery et al., "Numerical Recipes: Art of Scientific Computing", 3rd Edition, Cambridge Press.
  2. 2.J. M. Mathews and K. Fink, "Numerical Methods using MATLAB", 4th Edition, Prentice Hall Publication

Notes:

Source:

This course covers different concepts of numerical techniques of solving non-linear equations, system of linear equations, integration and differentiation, and ordinary and partial differential equations.
The main objective of this course is to provide concepts of numerical techniques for solving different types of equations and developing algorithms for solving scientific problems.
The laboratory exercises should consist programs for implementing non-linear equations, system of linear equations, interpolation and regression, numerical integration and differentiation, and solving ordinary and partial differential equations.
This syllabus follows the official BIT curriculum of Tribhuvan University. In case of any doubt or revision, the university’s published syllabus shall be considered authoritative.