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Models
It is a new system that is considerably easier than the system being modelled, but which saves the important points of the original machine. We might create a physical model of an airplane to check in a wind tunnel. It does not have additional things; but it has to have surfaces of the correct shape and size, in order to examine the important properties for this purpose. Mathematical models can take properties of machines that are important to us, and gives us to discover things about the machine much more conveniently than by manipulating the original system itself.
One of the hardest things about creating models is giving which aspects of the original operation to model and which ones to ignore. Several classic, dramatic engineering failures may be described to failing to model important points of the system.
Another most important dimension in modelling is whether the model is calculative or not. But, of course, there is likely to be some sort of delay and some error. We have to check whether to ignore that delay and error in our model and work it as if it were perfect.Once we have a model, we may use it in a variety of different aspects.
Worked example 1 Let's examine what happens when we compute the following Python code: def p(x, y): z = x*x - y return z + 1/z >>> p(1.0, 2.0) -2.0
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from urllib2 import urlopen # Open http://placekitten.com/ for reading on line 4! response = kittens.read() body = response[559:1000] # Add your ''print'' statement here!
How to write program on bit stuffing using python?
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