Teaching Scheme (in Hours)
Subject Credit : 4
Examination Scheme (in marks)
ESE Viva (V)
Syllabus Content Download
Modeling, Computers and error analysis : Mathematical modeling and engineering problem solving. Role of computers and software. Approximations and errors. Significant figures, accuracy and precision, Errors, round-off and truncation errors, error propagation.
Roots of Equations : Mathematical background, Bisection, Regula Falsi ,NR method,Secant , Successive approximation method, Budan’s Theorem, Barristow’s method, case studies.
Systems of linear algebraic equations: Mathematical background, Gauss elimination; pitfalls and techniques for improvement, matrix inversion and Gauss-Seidel methods, III Conditional equations,Predictor-Corrector methods,case studies.
Curve Fitting: Mathematical background, Least squares linear and polynomial regression, Lagrange interpolating polynomials. Spline interpolation, Case studies.
Numerical Integration : Newton-Cotes integration formulas; trapezoidal rule and Simpson’s rules: Interpolation, case studies.
Ordinary differential equations: Euler’s method, Runge-Kutta methods. General methods for boundary value problems,Automatic error monitoring and change of step size stability of solution. Case studies.
Frequency distributions, Data analysis, Expectations and moments, Co-relation and regression, Trend analysis, Seasonal effects, Cyclical fluctuation, Moving average, MSE, Predictions.
|1||Numerical Methods for engineers||S C Chapra and R P Canale||McGrow Hill International Edition|
|2||Numerical Methods for Scientific & Engineering Computation||M. K. Jain, S.R.K.|
|3||Introduction to Numerical Analysis||S. S. Sastry.||PHI|
|4||Numerical Methods in Science & Engineering Prog.||Dr. B. S. Grawal||Khanna Pub.|
|5||Computer Oriented Numerical Methods||R. S. Salaria||Khanna Publisher|
|6||Miller & Freund’s Probability and Statistics for Engineers||Richard A Johnson||PHI|
After learning the course the students should be able to:
- Apply Mathematical Modeling and for Engineering Problem Solving.
- Solve Mathematical Equations by various methods.
- Solve system of linear equations.
- Find Best Curve fitting for given data.
- Apply Numerical Integration.
- Solve Differential Equations.
- Understand Statistical Methods for Data Analysis.
Darshan Institute of Engineering & Technology is a leading institute offering undergraduate (B.E.), postgraduate (M.E.) and Diploma programs in engineering.