| Semester 1, 2023 Toowoomba On-campus | |
| Units : | 1 |
| School or Department : | School of Mathematics, Physics & Computing |
| Grading basis : | Graded |
| Course fee schedule : | /current-students/administration/fees/fee-schedules |
Staffing
Course Coordinator:
Overview
This course provides flexibility in honours and postgraduate programs to cater for the widely varying interests and chosen specialisations of students. Mathematicians need to be proficient in a wide range of mathematical concepts and techniques. Many of these are either only touched on or omitted from undergraduate programs. An opportunity to broaden the students' knowledge-base with more advanced concepts and techniques is provided in this course.
This course provides the opportunity for a student to pursue an area of study that will complement the other studies in the student's program. Typically the course will consist of specialised investigations extending knowledge and skills in one of the areas listed in the Topics section below, or another Topic where appropriate and where a supervisor is available.
Course learning outcomes
On successful completion of this course students will be able to:
- demonstrate advanced knowledge and skills in the complementary study area.
Topics
| Description | Weighting(%) | |
|---|---|---|
| 1. |
Students should nominate the topic they wish to study; and then email the Course Examiner to enquire whether the topic and a suitable supervisor will be available in their semester of study, and for formal approval to enrol. One of the following topics can be chosen. The content of the course may vary from student to student. The weighting of the sub-topics within this course depends on the topic chosen and will be discussed with the supervisor. 鈥� Operations Research: (prerequisite MAT2200 or MAT1200 or equivalent) This topic introduces and extends upon the methods and theory in Operations Research 2 MAT3201. Topics include inventory control theory, Markov Chains, Queuing theory, Dynamic programming and Simulation. Concepts in simulation are developed through the design of probabilistic simulation models for inventory and queueing problems. (This topic is not compatible with MAT3201) 鈥� Partial Differential Equations: (prerequisite ENM2600 or MAT2100 or MAT2500 or equivalent) PDEs are widely used as models of physical, biological and chemical processes as well as to simulate financial markets. This course introduces and extends the methods and theory in Harmony of Partial Differential Equations. Topics covered included: basic PDEs such as heat and wave equations, describes their properties, gives general solving methods and contains brief introduction to non-linear PDEs (note this course is not compatible with MAT3105) 鈥� Mathematics Education: This course is designed for students interested in expanding their knowledge in one or more areas of mathematics education. Topics could include: the role of language in learning and understanding mathematics; issues in adult, academic and everyday numeracy; fundamental constructs in mathematics education; history and philosophy of mathematics. 鈥� Wavelet Transformation and Artificial Neural Network in Environmental Modelling: Develop ANN models for predictive modelling and further apply wavelet transformation to enhance the performance of the forecasted values. In this context, the topic will (1) explore the basic theory of ANN and WT algorithm; (2) develop an ANN and a wavelet-hybrid ANN hybrid model; (3) analyse environmental data, generate simulations, and assess the model鈥檚 accuracy. Some programming in MATLAB, R or Python is assumed. 鈥� Numerical Computation: (prerequisite CSC1401 (or CSC2410) and MAT1102 (or ENM1600) or equivalent) Numerical Computation is used to determine approximate solutions to complex physical problems, which occur in: Finance, Astrophysics, Fluid dynamics and Atmospheric scent etc. This course introduces and extends the methods covered in MAT2409. Topics may include: Vector coding, MPI algorithms (Parallel Computation), Discrete methods for Differential Equations, Simulation, Shooting methods, and interpolation methods. (This topic is not compatible with MAT2409). |
100.00 |
Text and materials required to be purchased or accessed
Student workload expectations
To do well in this subject, students are expected to commit approximately 10 hours per week including class contact hours, independent study, and all assessment tasks. If you are undertaking additional activities, which may include placements and residential schools, the weekly workload hours may vary.
Assessment details
| Description | Group Assessment |
Weighting (%) | Course learning outcomes |
|---|---|---|---|
| Problem Solving | No | 50 | 1 |
| Report | No | 50 | 1 |