Year: 2015
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A brief summary of Model Considerations
Number of elements to consider when building models: Define model purpose when designing model. Model should be verified and validated. Designed by humans from specific perspective, may be flawed. Model only gives partial view of situation/system. Number of models required to gain full understanding of situation/system providing different views. Abstraction level required is key decision.
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Other Classification Systems
In addition to static and dynamic, models can also be defined as quantitative and qualitative. Quantitative models similar to numeric models quantify situation with facts and data Qualitative models shows structure of elements/components Other model classifications are hard and soft models. Hard models are like quantitative models and are based on facts and data. Soft models…
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Static or Dynamic Models
Models classified as either static or dynamic models. Static models tend not to change much, only if significant change in situation London tube map changes only when new line added powerful source of information/understanding if situation is constant Used in business environment to understand enterprise/system, simulation used to analyse behaviour of system. Most models are…
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Word, Visual and Mathematical Models
Word Models: Consist of words. Examples: a specification, an abstract Provide significant amount of information Can be structured in different ways Weakness: linear and not multi-dimensional – hard to provide complex relationships, can become unwieldy Visual Models: Type of picture – ‘a picture paints a thousand words’ Show a lot of information in small amount…
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Types of Models
Covered in previous lesson – classification of models rather than specific types. Continue categorising and classifying models. Role and use of several types of models with emphasis on Dynamic and Static models. Consider structural and functional relationships in complex systems. Simplifications usually unavoidable when modelling. Processes being considered can vary from simplistic to extremely complex,…
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Summary
In this lesson, we have identified and defined what a model is. Understanding systems does not stop with our particular field. Looked at models in broadest sense and when/how best to apply particular model. Importance of verification and validation.
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Steps to take when modelling
Brief overview of steps for tackling modelling process. What precisely is our problem and what do we want the model to do? Do we need a model at all? Perhaps it is too simple a task and we would sooner not waste time. Are similar models available? Can we buy one or use a pre-existing…
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System walkthrough and Consistency testing
System walkthrough Explaining model to another person/persons – enables modeller to focus on different aspects and to discover problems. Writing system documentation can have the same effect to by making to modeller look at model from different perspective. Consistency testing Check model produces similar results for input parameter values that have similar effects. Example: Network…
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Model Validation and Verification
Model is abstraction & consists of assumptions we make. In creation we remove unnecessary detail and focus on elements of system that are in important from desired performance point of view. Assumptions about system must be made during model construction therefore we must check that the model is a good fit. Process of robust model…