APP MTH 7035 - Modelling with Ordinary Differential Equations III
North Terrace Campus - Semester 1 - 2017
Differential equation models describe a wide range of complex problems in biology, engineering, physical sciences, economics and finance. This course focuses on ordinary differential equations (ODEs) and develops students' skills in the formulation, solution, understanding and interpretation of coupled ODE models. A range of important biological problems, from areas such as resource management, population dynamics, and public health, drives the study of analytical and numerical techniques for systems of nonlinear ODEs. A key aim of the course is building practical skills that can be applied in a wide range of scientific, business and research settings.
Topics covered are: analytical methods for systems of ODEs, including vector fields, fixed points, phase-plane analysis, linearization of nonlinear systems, bifurcations; general theory on existence and approximation of ODE solutions; biological modelling; explicit and implicit numerical methods for ODE initial value problems, computational error, consistency, convergence, stability of a numerical method, ill-conditioned and stiff problems.
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General Course Information
Course Details
Course Code APP MTH 7035 Course Modelling with Ordinary Differential Equations III Coordinating Unit Mathematical Sciences Term Semester 1 Level Postgraduate Coursework Location/s North Terrace Campus Units 3 Contact Up to 3 hours per week Available for Study Abroad and Exchange Y Prerequisites (MATHS 2101 and MATHS 2102) or (MATHS 2201 and MATHS 2202) Incompatible APP MTH 3013, APP MTH 3004 Assumed Knowledge MATHS 2104 Assessment Ongoing assessment 30%, Exam 70% Course Staff
Course Coordinator: Dr Luke Bennetts
Course Timetable
The full timetable of all activities for this course can be accessed from .
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Learning Outcomes
Course Learning Outcomes
Students who successfully complete the course should:- understand how to model time-varying systems using ordinary differential equations
- be able to identify and analyse stability of equilibrium solutions
- be able to numerically solve ordinary differential equations
- be able to analyse how the structure of solutions can change depending on a parameter
- understand the analytical solution theory for linear systems of ordinary differential equations
- appreciate the necessity of numerical and qualitative methods for analysing solutions for nonlinear systems
- have a detailed understanding of several ordinary differential equations models arising in physics, biology and chemistry, namely oscillator models, Lotka-Volterra competition and predator-prey models, Michaelis-Menton kinetics and SIR epidemic models
University Graduate Attributes
This course will provide students with an opportunity to develop the Graduate Attribute(s) specified below:
University Graduate Attribute Course Learning Outcome(s) Deep discipline knowledge
- informed and infused by cutting edge research, scaffolded throughout their program of studies
- acquired from personal interaction with research active educators, from year 1
- accredited or validated against national or international standards (for relevant programs)
all Critical thinking and problem solving
- steeped in research methods and rigor
- based on empirical evidence and the scientific approach to knowledge development
- demonstrated through appropriate and relevant assessment
1,2,4,6 Teamwork and communication skills
- developed from, with, and via the SGDE
- honed through assessment and practice throughout the program of studies
- encouraged and valued in all aspects of learning
1,4,6 Career and leadership readiness
- technology savvy
- professional and, where relevant, fully accredited
- forward thinking and well informed
- tested and validated by work based experiences
all Self-awareness and emotional intelligence
- a capacity for self-reflection and a willingness to engage in self-appraisal
- open to objective and constructive feedback from supervisors and peers
- able to negotiate difficult social situations, defuse conflict and engage positively in purposeful debate
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Learning Resources
Required Resources
None.Recommended Resources
1. Butcher, John. Numerical Methods for Ordinary Differential Equations (Wiley, 2008)
2. Chicone, Carmen. Ordinary Differential Equations with Applications (Springer, 2006)
3. Dahlquist, Germund and Bjorck, Ake. Numerical Methods (Dover, 2003)
4. de Vries, Gerda et al. A Course in Mathematical Biology (SIAM, 2006)
5. Edelstein-Keshet, Leah. Mathematical Models in Biology (SIAM, 2005)
6. Strogatz, Steven. Nonlinear Dynamics and Chaos (Perseus, 2001)Online Learning
This course uses MyUni (Canvas) exclusively for providing electronic resources, such as lecture notes, assignment papers, sample