The use of mathematical models has grown rapidly in recent years, owing to the advent of cheap and powerful computers, expanding from applications in the physical and earth sciences to the biological and environmental sciences, and now into industry and commerce.
In this course we study:
- The process of starting with an initial succinct non-mathematical description of a problem
Formulate associated mathematical models. - Introduce new mathematical techniques and then determine and interpret solutions that are useful in a real life context.
- General computational and mathematical techniques and strategies will be introduced by examining specific scientific and industrial problems.
The topics to be covered in this course include:
- Model type selection and formulation
- Data analysis techniques (time/space and frequency domain)
- State Space and Transfer Function Models
- Model Structure Identification
- Testing and Sensitivity Analysis
Computations will be done using modern high level scientific computing environments such as SCILAB or PYTHON.
Note: Graduate students attend joint classes with undergraduates but are assessed separately.
Learning Outcomes
Upon successful completion, students will have the knowledge and skills to:
On satisfying the requirements of this course, students will have the knowledge and skills to:
1. Design a model based on the basic processes and behaviour of a system and different ways of representing them
2. Evaluate the issues in building and evaluating models, taking into account their purpose and prior knowledge
3. Explain and use some important modelling tools (transfer function, state space, frequency-domain and DE-based models as well as data analysis techniques)
4. Discuss the role of modelling in both industry and science
5. Explain sensitivity and uncertainty analysis techniques
Indicative Assessment
Assessment will be based on:
- Exam (40%; LO 1, 2, 3, 4, 5)
- Project designing and evaluating a model for a selected system (30%; LO 1, 2)
- Three assignments demonstrating ability to apply techniques (10% each; LO 2, 3, 5)
The ANU uses Turnitin to enhance student citation and referencing techniques, and to assess assignment submissions as a component of the University's approach to managing Academic Integrity. While the use of Turnitin is not mandatory, the ANU highly recommends Turnitin is used by both teaching staff and students. For additional information regarding Turnitin please visit the ANU Online website.
Workload
Three hours per week and regular workshops/computer labs.Requisite and Incompatibility
You will need to contact the Mathematical Sciences Institute to request a permission code to enrol in this course.
Fees
Tuition fees are for the academic year indicated at the top of the page.
Commonwealth Support (CSP) Students
If you have been offered a Commonwealth supported place, your fees are set by the Australian Government for each course. At ANU 1 EFTSL is 48 units (normally 8 x 6-unit courses). More information about your student contribution amount for each course at Fees.
- Student Contribution Band:
- 1
- Unit value:
- 6 units
If you are a domestic graduate coursework student with a Domestic Tuition Fee (DTF) place or international student you will be required to pay course tuition fees (see below). Course tuition fees are indexed annually. Further information for domestic and international students about tuition and other fees can be found at Fees.
Where there is a unit range displayed for this course, not all unit options below may be available.
| Units | EFTSL |
|---|---|
| 6.00 | 0.12500 |
Course fees
- Domestic fee paying students
| Year | Fee |
|---|---|
| 2023 | $4320 |
- International fee paying students
| Year | Fee |
|---|---|
| 2023 | $6180 |
Offerings, Dates and Class Summary Links
ANU utilises MyTimetable to enable students to view the timetable for their enrolled courses, browse, then self-allocate to small teaching activities / tutorials so they can better plan their time. Find out more on the Timetable webpage.
Class summaries, if available, can be accessed by clicking on the View link for the relevant class number.
Second Semester
| Class number | Class start date | Last day to enrol | Census date | Class end date | Mode Of Delivery | Class Summary |
|---|---|---|---|---|---|---|
| 5955 | 24 Jul 2023 | 31 Jul 2023 | 31 Aug 2023 | 27 Oct 2023 | In Person | N/A |
