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Principles of Modeling

Principles of Modeling. Principle 1: Model Simple, Think complicated. Model. Rigorous A rgumentation Critical Thinking Analysis. Principle 1: Model Simple, Think complicated. Routine use. Human interaction. Routine decision support. System investigation & improvement.

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Principles of Modeling

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  1. Principles of Modeling

  2. Principle 1: Model Simple, Think complicated Model Rigorous Argumentation Critical Thinking Analysis

  3. Principle 1: Model Simple, Think complicated Routine use Human interaction Routine decision support System investigation & improvement Decision automation Models that provide insight

  4. Principle 2: be parsimonious – start small & add • KISS [keep it simple, stupid] • Ball Example

  5. Principle 3: divide, conquer, avoid mega models “Beware of general purpose, grandiose models that try to in incorporate practically everything. Such models are difficult to validate, to interpret, to calibrate statistically and, most importantly, to explain. You may be better off not with one big model but with a set of simpler models”. Raiffe 1982 Example: manufacturer of packaging items that wishes to provide a better service to geographically scattered customers. Demand model Production model Customer priorities Truck capacities

  6. Principle 4: use metaphors, analogies and similarities Look for analogies based on previous experience – on well developed logical structures that worked before. Electricity Example • Water flowing through pumps, valves and reservoirs - batteries • People moving through crowd - resistance

  7. Principle 5: do not fall in love with data • The model should drive the data, not vice-versa • Data mining and data grubbing • Beware of data provided in a plate • Data are just a sample • Avoid using the same data to build and test a model

  8. Principle 6: Model building may feel like muddling through “develop their models, not in one burst, but over an extended period of time …” “…guided by analogies, drawings, doodling …” 60% time – model structure 30% time – problem context & model assessment 10% time – model realization Willemain 1995

  9. Summary • Principle 1: Model Simple, Think complicated • Principle 2: be parsimonious – start small & add • Principle 3: divide, conquer, avoid mega models • Principle 4: use metaphors, analogies and similarities • Principle 5: do not fall in love with data • Principle 6: Model building may feel like muddling through

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