Runge-Kutta Method in Python and MATLAB
- Course provided by Udemy
- Study type: Online
- Starts: Anytime
- Price: See latest price on Udemy
In this video tutorial, the theory of Runge-Kutta Method (RK4) for numerical solution of ordinary differential equations (ODEs), is discussed and then implemented using MATLAB and Python from scratch. As an example, the well-know Lotka-Volterra model (aka. the Predator-Prey model) is numerically simulated and solved using Runge-Kutta 4th order (RK4), in both languages, Python and MATLAB.
Who this course is for:
- Applied Math and Science Students
- Engineering Students
- Anyone Interested in Numerical Computation
- Software Engineers and Programmers
- 02:41Introduction to Runge-Kutta Method
- 03:26The Lotka-Volterra Model
- 03:09Implementation of Lotka-Volterra System in MATLAB
- 07:25Implementation of RK4 in MATLAB
- 06:44Wrapping things up: Applying solver to model
- 02:44Implementation of Lotka-Volterra System in Python
- 03:47Implementation of RK4 in Python
- 05:47Wrapping things up: Applying solver to model
The Yarpiz project is aimed to be a resource of academic and professional scientific source codes and tutorials, specially Computational Intelligence, Machine Learning, and Evolutionary Computation. Beside video tutorials, various source codes are available to download, via Yarpiz website.
The word Yarpiz (pronounced /jɑrpəz/) is an Azeri Turkish word, meaning Pennyroyal or Mentha Pulegium plant.
Mostapha Kalami Heris was born in 1983, in Heris, Iran. He received B.S. from Tabriz University in 2006, M.S. from Ferdowsi University of Mashad in 2008, and PhD from Khaje Nasir Toosi University of Technology in 2013, all in Control and Systems Engineering.
Dr. Kalami is also co-founder of, executive officer of, and an instructor in FaraDars, an online education organization located in Iran. Also, he is a member of Yarpiz Team, which is provider of academic source codes and tutorials. He is mostly interested in the computer programming, machine learning, artificial intelligence, meta-heuristics and control engineering topics.