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Prediction of demand is one of most important problems for managers and planners.
Next, the prediction of demand for the distant future may be very inaccurate.
In this case, as the prediction of demand theory, the demand for groundwater protection decreases as household income increases.
In this paper, we present an iterative method for prediction of demand with normally distributed and independent variables of n-dimensional space and the demand space is a nonlinear function, in general.
Hence the prediction of demand at the level of the individual vehicle model carries less political interest than forecasting at the somewhat more aggregate level, whereby cars are grouped according to, e. g., their make, size, fuel economy or exhaust emissions.
Hence the prediction of demand at the level of the individual vehicle model variant carries less political interest than forecasting at the somewhat more aggregate level, whereby cars are grouped according to, e. g., their make, size, fuel economy or exhaust emissions.
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Social media data from Twitter and elsewhere is also a huge opportunity for improving predictions of demand patterns.
Such a scenario would assume that network planners generate relatively precise predictions of demand in a cell.
A well-functioning health system requires an adequate number of capable, motivated and well-supported health workers; policy makers often ask how many physicians they should produce in order to meet future health needs [ 5]; accurate predictions of demand for health workers facilitate better production plans.
In [10], efficient operation of a power system is defined based on prediction of power demand- how much demand, where and when it is required to maintain efficiency of power grid.
To improve ATMs' cash demand forecasts, this paper advocates the prediction of cash demand for groups of ATMs with similar day-of-the week cash demand patterns.
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