Modelling Dynamic Systems - CMI3502

Assessment 1: Other

Learners will undertake a series of formative exercises in the practical sessions. Feedback, advice and guidance will be provided for these exercises.

Other

Assessment 1: Project Work

Individually design and develop a simulation model of a dynamic system. The learner will demonstrate their model to their tutor and report all design considerations and testing strategies employed, including any model optimisations that have been incorporated. Relevant model documentation is required.

Project Work

Assessment 2: Written Assignment

2 online 20 minute in-class tests, each worth 20% of the summative mark.

Written Assignment

<p>Dynamic systems of inter-related entities are becoming more commonplace as computational resources are miniaturised. Examples of dynamic systems include information technology network infrastructure for communications, computational devices that have mobility, or even the inner workings of a modern central processing unit (CPU). As physical devices adopt more technology, become more ubiquitous, and contribute to inter-connected ‘smart’ environments, there is a need to be able to understand, model and design innovative solutions that embody, and take into account, these dynamic characteristics. This module will enable you to select the most appropriate method of modelling a dynamic system, before simulating its behaviour and then optimising its performance.</p>

Requirements apply to students taking an IET accredited course. Please refer to the Programme Specification Document for details.

School of Computing and Engineering

<p>https://library.hud.ac.uk/readinglists/CMI3502</p>

Computing and Information Systems

CMI3502 - Modelling Dynamic Systems

Modelling Dynamic Systems

Synthesise a number of approaches to design, implement and optimise a dynamic systems model.

Critically describe dynamic systems, their modelling, simulation and optimisation.

Design and critically evaluate a simulation model of a dynamic system using a simulation environment.

Evaluate current practices in the development of dynamic system models and related experimental and validation issues.