B - Modelling and simulation

B.1 The basic model

B.1.1 Define the term computer modelling.
B.1.2 Identify a system that can be modelled.
B.1.3 Identify the variables required to model a given system.
B.1.4 Describe the limitations of computer (mathematical) models.
B.1.5 Outline sensible grouping for collections of data items, including sample data.
B.1.6 Design test-cases to evaluate a model.
B.1.7 Discuss the effectiveness of a test-case in a specified situation.
B.1.8 Discuss the correctness of a model by comparing generated results with data that were observed in the original problem.

B.2.1 Define the term simulation.
B.2.2 Explain the difference between a model and a simulation.
B.2.3 Describe rules that process data appropriately and that produce results.
B.2.4 Discuss rules and data representations and organization.
B.2.5 Construct simple models that use different forms of data representation and organization.
B.2.6 Design test-cases to evaluate a simulation program.
B.2.7 Outline the software and hardware required for a simulation.
B.2.8 Describe changes in rules, formulae and algorithms that would improve the correspondence between results and observed data.
B.2.9 Construct examples of simulations that involve changes in rules, formulae and algorithms.
B.2.10 Describe changes in data collection that could improve the model or simulation.
B.2.11 Discuss the reliability of a simulation by comparing generated results with data that were observed in the original problem.
B.2.12 Outline the advantages and disadvantages of simulation in a given situation rather than simply observing a real-life situation.
B.2.13 Discuss advantages and disadvantages of using a simulation for making predictions.

B.3.1 Define the term visualization.
B.3.2 Identify a two-dimensional use of visualization.
B.3.3 Outline the memory needs of 2D visualization
B.3.4 Identify a three-dimensional use of visualization.
B.3.5 Outline the relationship between the images in memory and the 3D visualization.
B.3.6 Discuss the time and memory considerations of 3D animation in a given scenario.

B.4.1 Outline the use of genetic algorithms.
B.4.2 Outline the structure of neural networks.
B.4.3 Compare applications that use neural network modelling.
B.4.4 Compare different ways in which neural networks can be used to recognize patterns.
B.4.5 Identify the key structures of natural language.
B.4.6 Discuss the differences between human and machine learning when related to language.
B.4.7 Outline the evolution of modern machine translators.
B.4.8 Describe the role of chatbots to simulate conversation.
B.4.9 Discuss the latest advances in natural language processing.

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