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Pitfalls in computer simulation
Though generally avoided in computer simulations, in strict logic the rules governing floating point arithmetic even apply. For illustration, the probabilistic risk analysis of factors finding the success of an oilfield exploration program engages combining samples from various statistical distributions by using the Monte-Carlo methods. These comprise normal, lognormal, triangular and the uniform distributions. Conversely, a sample from a distribution cannot maintain more important figures than were representing in the data or estimates which established those distributions. Therefore, abiding through the rules of important arithmetic, no result of a simulation can maintain more important figures than were representing in the input parameter along with the least number of important figures. If, for illustration the net/gross ratio of oil-bearing strata is identified to only one important figure, then the consequence of the simulation cannot be more exact than one major figure, though it may be presented as having three or four important figures.
Automatic Data Capture There are numerous techniques available to collect data automatically without the need for manual entry. Manual entry is slower, more costly (need to emp
what is normalization transformation?why is it needed and important?give simple example also.
The development of CAD had little consequence on CNC initially because of the various abilities and file formats used through drawing and machining programs. Conversely, as Compute
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Program of PERT in c language
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Determine the transformation matrix for the reflection about the line y = x. Solution: The transformation for mirror reflection regarding to the line y = x, comprises the subs
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