This course gives you an introduction to modeling methods and simulation tools for a wide range of natural phenomena. The different methodologies that will be presented here can be applied to very wide range of topics such as fluid motion, stellar dynamics, population evolution, ... This course does not intend to go deeply into any numerical method or process and does not provide any recipe for the resolution of a particular problem. It is rather a basic guideline towards different methodologies that can be applied to solve any kind of problem and help you pick the one best suited for you.
ofrecido por
Simulation and modeling of natural processes
Universidad de GinebraAcerca de este Curso
ofrecido por

Universidad de Ginebra
Founded in 1559, the University of Geneva (UNIGE) is one of Europe's leading universities. Devoted to research, education and dialogue, the UNIGE shares the international calling of its host city, Geneva, a centre of international and multicultural activities with a venerable cosmopolitan tradition.
Programa - Qué aprenderás en este curso
Introduction and general concepts
This module gives an overview of the course and presents the general ideas about modeling and simulation. An emphasis is given on ways to represent space and time from a conceptual point of view. An insight of modeling of complex systems is given with the simulation of the grothw and thrombosis of giant aneurysms. Finally, a first class of modeling approaches is presented: the Monte-Carlo methods.
Introduction to programming with Python 3
This module intends to provide the most basic concepts of high performance computing used for modeling purposes. It also aims at teaching the basics of Python 3 which will be the programming language used for the quizzes in this course.
Dynamical systems and numerical integration
Dynamical systems modeling is the principal method developed to study time-space dependent problems. It aims at translating a natural phenomenon into a mathematical set of equations. Once this basic step is performed the principal obstacle is the actual resolution of the obtained mathematical problem. Usually these equations do not possess an analytical solution and advanced numerical methods must be applied to solve them. In this module you will learn the basics of how to write mathematical equations representing natural phenomena and then how to numerically solve them.
Cellular Automata
This module defines the concept of cellular automata by outlining the basic building blocks of this method. Then an insight of how to apply this technique to natural phenomena is given. Finally the lattice gas automata, a subclass of models used for fluid flows, is presented.
Reseñas
- 5 stars48,22 %
- 4 stars34,95 %
- 3 stars9,38 %
- 2 stars3,88 %
- 1 star3,55 %
Principales reseñas sobre SIMULATION AND MODELING OF NATURAL PROCESSES
Great course, it presents mathematical models and implementations to simulate behaviors of natural systems with the right level of difficulty. It offer awesome insights to solve and optimize code.
Extremely good course with excellent python codes for interesting applications
Week 5 and 6 where harder to follow and the projects where more complicated to understand (even though it shows that effort were put into them)
In depth analysis of simulating processes, from mathematics to algorithms.
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