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Chapter 8: Models and Simulations. By Mohammad Ezmir. What is a model?. Models are simplified representations of real concepts and events , used to aid understanding or make predictions about outcomes without actually testing them.

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Chapter 8 models and simulations

Chapter 8:Models and Simulations

By Mohammad Ezmir


What is a model
What is a model?

Models are simplified representations of real concepts and events, used to aid understanding or make predictions about outcomes without actually testing them.

For example, a teacher’s classroom scale model of the planets helps understanding of the solar system and planetary orbits.

(Gray, 2012, pg. 166)


Computer models are used to model two main types of event
Computer models are used to model two main types of event:

  • Those which are difficult or impossible to observe.

    E.g. birth and death of star in space

  • Events which are expensive or dangerous to test by experimentation

    E.g. the effects of car crashes on the passengers

(Gray, 2012, pg. 166)


Variables

Computer models

Predictions

Decisions

Processes

(Gray, 2012, pg. 166)


Application of models
Application of models

  • Transportation models

  • Structural models

  • Drug interaction models

  • Car crash models

  • Climate models

(Gray, 2012, pg. 166)


Why use models
Why use models?

  • “What if” scenarios

  • Cheaper and require fewer materials

  • Safer

  • Practical

  • Only option in some cases

  • Repetition

(Gray, 2012, pg. 168)


Financial models
Financial models

This is when artificial intelligence is used to make decisions in financial markets

Advantage:

  • Thousands of complex calculations in seconds

    Disadvantage:

  • False predictions can result in major losses

    (look at case study on page 169)

  • Integrity of the model, data and result

(Gray, 2012, pg. 169)


Feedback loops
Feedback loops

Feedback loops can be used to improve the accuracy of a system by using previous results as input.

(Gray, 2012, pg. 173)


Cause of simplification
Cause of Simplification

  • Lack of scientific understanding

  • Lack of available data

  • Lack of available computing power can limit computer model complexity

(Gray, 2012, pg. 173)


Key points so far
Key points so far…

  • All computer models are based on scientific and mathematical principles

  • All computer models are simplifications of reality

  • Models allow time to be sped up or slowed down

  • Models are used to make predictions

(Gray, 2012, pg. 173)


High performance computing
High Performance Computing

Supercomputers achieve tremendous speeds by using parallel processing techniques

(Gray, 2012, pg. 176)


Parallel processing
Parallel processing

  • Centralised processing involves multiple processors installed in the same computer system. (e.g. IBM Blue Gene)

  • Distributed processing uses multiple separate computers connected by a network. (e.g. [email protected])

(Gray, 2012, pg. 176)


Visualisation
Visualisation

Main advantage:

  • Large amount of information can be displayed in a compact form, using colour and animation to help distinguish between different types of data and changes over time

(Gray, 2012, pg. 177)


What is a computer simulation
What is a computer simulation?

A computer simulator provides the user with experience of a real life situation by combining computer models of the world with realistic input and output devices and realistic graphics

(Gray, 2012, pg. 180)


Application of simulators
Application of simulators

  • Flight simulator

  • Driving simulator

  • Ship simulator

  • Train simulator

  • Space craft simulator

  • Combat simulator

(Gray, 2012, pg. 180)


Advantages of simulators
Advantages of simulators

  • Unusual or rare events can be programmed to happen as often as required

  • User can practise in these situations without any fear of loss or damage to people or equipment

  • Saves time

  • Long term cost savings

(Gray, 2012, pg. 180)


Disadvantages of simulators
Disadvantages of simulators

  • Not an exact reproduction of the real world due to simplifications

  • Integrity of data in the model

  • Unable to recreate pressure and fear of real life events

(Gray, 2012, pg. 180)


References
References

Gray, S. (April 23, 2012). Information Technology in a Global Society. Charleston, SC : USA


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