Upcoming SlideShare
×

Thanks for flagging this SlideShare!

Oops! An error has occurred.

×
Saving this for later? Get the SlideShare app to save on your phone or tablet. Read anywhere, anytime – even offline.
Standard text messaging rates apply

# Orm

188

Published on

0 Likes
Statistics
Notes
• Full Name
Comment goes here.

Are you sure you want to Yes No
• Be the first to comment

• Be the first to like this

Views
Total Views
188
On Slideshare
0
From Embeds
0
Number of Embeds
0
Actions
Shares
0
1
0
Likes
0
Embeds 0
No embeds

No notes for slide

### Transcript

• 1. Model<br />Model is simplified representation of relevant entities of some specific reality and their characteristics.<br />In general model can be classified as follows:<br />
• Iconic models
• 2. Analogue models
• 3. Symbolic models
1. Iconic Model<br />Iconic Model is representation of some specific entity.<br />ClassificationIconic Models can be represented in: - Two Dimensions <br />Example: drawings, photos etc.<br />- Three Dimensions: <br />Example: scale model<br />2. Analogue Model<br />Analogue Model uses a set of properties to represent the properties of real life system.<br />Example:<br />Through diagrams<br />ClassificationAn Analogue Model can be built through: - Two Dimensional Visualization:<br /> Charts, Graphs, Diagrams- Three Dimensional Visualization: <br />Analogue Devices<br />3. Symbolic Model<br />Symbolic Model is representation of entities of a system through symbols.Symbols can be: - mathematical- logical- computer programs<br />Deterministic Model <br />Model which provides a close-form solution to a problem and it does not contain element of probability. Deterministic models involve optimization.<br />Examples<br />Linear programming, non linear programming, network optimization, dynamic programming<br />Stochastic Model <br />This model contains the element of probability.<br />Examples:<br />Queuing theory, stochastic processes, reliability theory, and stimulation techniques.<br />