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Typesof Modeling Oscar Julian Sepulveda Ruiz Code 2070617
1. Mental Model: First perception of the problem at mental. It is the first play of ideas that are generated intuitively on the problem at hand.
2. Verbal Model: it is the first attempt to formalize language characteristics of the problem. In this model performsfirstformal approach to the problem.
3. Graphic Model: the set of images and graphics support to help locate the functional relations that prevail in system to be studied.
4. Physical Model: consists of an assembly that can operate as a real testbed. They are usually laboratory-scale simplifications that allow more detailed observations. Not always easy to build.
5. Mathematical Model: seeks to formalize in mathematical language relations and variations you want to represent and analyze.Normally expressed as differential equations andthis reason may also be known as differential model.
5.1Analytical Model: arises when the differential model has solution. This is not always possible, especially when differential models are formulated on differential Partial. 5.2 Numerical Model: arises when using numerical techniques to solve differential models. They are very common when differential model has no analytical solution. 5.3 Computational Model: refers to a program computer that allows analytical or numerical models can be solved more quickly. They are very useful for implement numerical models because these are based on iterative process can be long and tedious.

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Types of modeling

  • 1. Typesof Modeling Oscar Julian Sepulveda Ruiz Code 2070617
  • 2. 1. Mental Model: First perception of the problem at mental. It is the first play of ideas that are generated intuitively on the problem at hand.
  • 3. 2. Verbal Model: it is the first attempt to formalize language characteristics of the problem. In this model performsfirstformal approach to the problem.
  • 4. 3. Graphic Model: the set of images and graphics support to help locate the functional relations that prevail in system to be studied.
  • 5. 4. Physical Model: consists of an assembly that can operate as a real testbed. They are usually laboratory-scale simplifications that allow more detailed observations. Not always easy to build.
  • 6. 5. Mathematical Model: seeks to formalize in mathematical language relations and variations you want to represent and analyze.Normally expressed as differential equations andthis reason may also be known as differential model.
  • 7. 5.1Analytical Model: arises when the differential model has solution. This is not always possible, especially when differential models are formulated on differential Partial. 5.2 Numerical Model: arises when using numerical techniques to solve differential models. They are very common when differential model has no analytical solution. 5.3 Computational Model: refers to a program computer that allows analytical or numerical models can be solved more quickly. They are very useful for implement numerical models because these are based on iterative process can be long and tedious.