Modelling and Simulation

6 EC

Semester 1, period 2

5132MOSI6Y

Owner Bachelor Future Planet Studies
Coordinator Eldar Rakhimberdiev
Part of Minor Earth and Ecology, year 1Bachelor Biologie, year 3Bachelor Bèta-gamma, major Biologie, year 3Bachelor Bèta-gamma, major Aardwetenschappen, year 3Bachelor Future Planet Studies, major Aardwetenschappen, year 3Bachelor Future Planet Studies, major Future Earth, year 3

Course manual 2022/2023

Course content

The course provides a detailed introduction to simulation and modelling techniques commonly used in the earth and natural sciences. The course is primarily intended for students from the Future Planet Studies bachelor’s program but is equally useful for those wishing to apply simulation and modelling techniques in related fields. Students in this course are required to have had experience in basic programming in R, and acquaintance with classical mathematical models in geo-ecosystems or related fields such as ecology and/or evolution.

Study materials

Literature

  • Suggested reading material will be provided . This material is not necessary for completing the worksheets, it will be provided as extra enrichment and/or extra support.

Syllabus

  • This is a hands on course. To learn how to analyze data and develop basic and more advanced models students will be spending most of the time programming. After a new modelling technique is introduced in a lecture. Students start programming their own basic models that become increasingly more advanced. Every week students also develop small group research projects that they present to the rest of the group.

Software

  • R

  • Students will need to bring their personal laptops to the lectures, to the practicals and to the exam.  
    R needs to be installed before the first lecture!
     

Objectives

  • The students will be acquainted with a range of simulation and modelling techniques, including differential equations and agent-based models; by the end of the course, students will be able to decide which of these is most appropriate for addressing a specific scientific problem.
  • The students will develop practical expertise in the process of abstracting real systems into different modeling frameworks; by the end of the course, students will be able to translate a true scientific question into a model.
  • The students will gain hands-on simulation exercises; by the end of the course, students will be able to translate a model into a computer simulation.
  • The students will gain experience carrying out critical and creative scientific research with models and simulations; by the end of the course, students will be able to analyze a scientific problem by confronting different assumptions and abstractions in their simulations. 

Teaching methods

  • Lecture
  • Seminar
  • Laptop seminar
  • Computer lab session/practical training
  • Presentation/symposium
  • Self-study

Simulation and modelling in natural sciences require both skills (i.e., programming, developing algorithms, and solving equations) and techniques (i.e., the ability to recognise what is important and needs to be represented in the model, and what can and should be left out). Because this is a course designed for beginners, focus is given to both aspects— the technical side of constructing models and the ability to identify appropriate degrees of abstraction. 

Because there is no absolute set of rules that can universally be prescribed for insuring successful modelling results; students will be confronted with realistic and concrete hands-on modelling exercises throughout the course through which they can gain proficiency in the process of abstracting real systems into models and other practical expertise relevant to modelling and simulation. This will also support the development of each student's personal understanding and intuition, providing them with foundations for critical and creative problem solving in the natural sciences through simulation and modelling.

Learning activities

Activity

Number of hours

Lecture

16

Laptopcollege

74

Exam

3

Self study

67

Attendance

Programme's requirements concerning attendance (OER-B):

  • Participation in fieldwork is compulsory and cannot be replaced by assignments or other courses.
  • In case of practical sessions, the student is obliged to attend at least of 90% of the sessions and to prepare himself adequately, unless indicated otherwise in the course manual. In case the student attends less than 90%, the practical sessions should be redone entirely.
  • In case of tutorials/seminars with assignments, the student is obliged to attend at least 7 out of 8 seminars and to prepare thoroughly for these meetings, unless indicated otherwise in the course manual. If the course has more than 8 seminars, the student can miss up to 1 extra meeting for every (part of) 8 tutorials/seminars. If the students attends less than the mandatory tutorials/seminars, the course cannot be completed.

Additional requirements for this course:

  • Attendance in the lectures is required unless special approval for absence has been given.
  • Practical lessons: each student needs to be present and well prepared for at least 90% of the practical classes. In case the student missed more than 10% of the practical classes, he/she has to re-take the practical unless the exam committee decides on providing a practical-replacing assignment.
  • In special cases, a student can receive an exemption for (part of) the obligatory components of a course. The exam committee judges the requests for an exemption.

Assessment

Item and weight Details

Final grade

Tentamen digitaal

Student final grade will be based on the score of the final exam (40%), in class assignments (15%), homework (20%) and small group research projects (25%). The score of the exam cannot be less than 4.5, and the assignments will only be included in the final grade if: a) the exam mark falls between 4.5 and 5.5, and b), if the final grade after inclusion of the assignments is higher. In such cases the final grade will never be higher than 6.0.

Students that were enrolled in the course in previous years

For students that are enrolled in the course for the 2nd/3rd/etc. time, it is still mandatory to complete all components

Inspection of assessed work

Contact the course coordinator to make an appointment for inspection.

Up to 20 working days after the announcement of the result students have the right to inspect their work. Students can make an appointment with the course coordinator, Dr. Eldar Rakhimberdiev

Fraud and plagiarism

The 'Regulations governing fraud and plagiarism for UvA students' applies to this course. This will be monitored carefully. Upon suspicion of fraud or plagiarism the Examinations Board of the programme will be informed. For the 'Regulations governing fraud and plagiarism for UvA students' see: www.student.uva.nl

Course structure

Week 1 - Descriptive models 

  • Intro to Modeling and Simulation of dynamical systems in the Earth and Natural sciences;
  • Intro to descriptive models;
  • Linear models, generalised linear models, variable and model selection, multimodel inference.

Week 2 first half- Linear programming

  • simple optimisation tasks - crop distribution;
  • linear programming for conservation planning.

Week 2 second half - Simple compartmental models

  • Process modelling. Top down approach - simple compartmental models;
  • Ordinary differential equations, exponential and logistic population growth models, Continuous time LV model - equilibria;
  • Discrete time - population growth - Age-structured populations.

Week 3 first half - Advanced compartmental models

  • Epidemiological models - SI, SIR and their extensions;
  • Hydrological models.

Week 3 second half - From population to individual - cellular automates

  • Forest fires and fire breaks;
  • Spatially explicit epidemiological models.

Week 4 - Individual-based models

  • Individual-based epidemiological models
  • Individual-based models in NetLogo.

Week 4 last day - Final exam

* Note: Minor shifts in the schedule may take place  during the course (with early notice). In any event, these will not have effect on the basic structure or design of the course.

Timetable

The schedule for this course is published on DataNose.

Additional information

Early requirements:

1) Experience with basic programming in R

2) Software and personal laptop:  Students will need to bring their personal laptops to the lectures, practical’s and the exam. R needs to be installed before the first meeting (for assistance see below). 

 

We vinden het belangrijk dat je je op de UvA en bij Future Planet Studies veilig voelt. Krijg je onverhoopt te maken met ongewenst gedrag of voel je je onveilig, dan kun je terecht bij verschillende personen. Je melding wordt altijd vertrouwelijk behandeld. Kijk op onze website voor meer informatie over waar en bij wie je terecht kunt.

It is important that everyone feels safe at the UvA and Future Planet Studies. We are committed to provide social safety and we offer various forms of support for people experiencing inappropriate or unsafe situations. Consult the UvA website or Future Planet Studies Canvas page for more information and contact info.

Last year's student feedback

Last year (2021-2022) we have provided completely new course. Students gave gave it  8.6/10 (the average assessment of the course).

Contact information

Coordinator

  • Eldar Rakhimberdiev