MAS6446 Mathematical methods and modelling of natural systems
|Semester 2, 2021/22||20 Credits|
|Lecturer:||Dr Nils Mole||Timetable||Reading List|
Mathematical modelling enables insight in to a wide range of scientific problems. This module combines Mathematical Methods (MAS325), where there is an emphasis on solving problems that involve small parameters, which may be difficult to solve analytically or computationally, and Modelling of Natural systems (MAS414), where there is an emphasis on the practical application of methods, combining analytical and computational approaches.
There are no prerequisites for this module.
No other modules have this module as a prerequisite.
- Integral methods and differential equations: Dirac δ-function, Fourier and Laplace transforms, applications to differential equations, Green functions.
- Asymptotic expansions: algebraic equations with small parameter, asymptotic expansion of functions defined by integrals.
- An introduction to chaotic dynamics.
- Machine learning methods to retrieve forest biophysical parameters.
- A stochastic approach to modelling disease spread.
- To develop methods for solving differential equations using integral transforms and representations.
- To introduce asymptotic methods for solving algebraic equations.
- To introduce asymptotic methods for evaluating integrals.
- develop students’ skills in comprehending problems, formulating them mathematically and obtaining solutions by appropriate methods.
- provide practical demonstrations of how mathematical modelling may be used to gain insight in to the dynamics of natural systems.
- build on mathematical methods (ordinary/partial differential equations, linear stability analysis, scientific computing in Python), and expose students to how they can be used to model natural systems.
Learning outcomesBy the end of the unit, a candidate will 1. be familiar with the ideas of mathematical modelling and understand the utility of mathematical modelling to understand natural phenomena (QAA benchmark for mathematics, 5.4v); 2. be able to formulate a mathematical model that represents the dynamics of a natural system and apply appropriate methods to obtain solutions (QAA benchmark for mathematics, 5.4v); 3. be able to gain insight in to a natural system through the application of mathematical modelling techniques; 4. recognise how mathematical methods may be used to model natural systems.
32 lectures, no tutorials, 9 practicals
MAS325: Exam 50%
MAS414: Three pieces of coursework 3 x 15%, one oral presentation 5%.
|C||Bender and Orszag||Advanced Mathematical Methods For Scientists And Engineers I: Asymptotic Methods and Perturbation Theory||515.350245 (B)||Blackwells||Amazon|
|C||Hastie T, Tibshirani R, Friedman JH||The Elements of Statistical Learning: Data Mining, Inference, and Prediction||006.31 (H)||Blackwells||Amazon|
|C||Murray JD||Mathematical Biology I and II||570.15118 (M)||Blackwells||Amazon|
|C||Strogatz SH||Nonlinear dynamics and chaos: with applications to physics, physics, biology, chemistry, and engineering||531.3 (S)||Blackwells||Amazon|
(A = essential, B = recommended, C = background.)
Most books on reading lists should also be available from the Blackwells shop at Jessop West.