This research aims to predict the level of air pollution with a set of data used to make predictions through them and to obtain the best prediction using several models and compare them and find the appropriate solution.
In this research, we developed an algorithm to measure
the quality of processed digital video, with no
information about the video before processing, to know
how much the video was distorted as a result of
processing
Decision making process have to be much more accurate and careful. Therefore, decision makers depend on what-if analysis systems to predict an impact of a specific scenario.
Usually, previous what-if analysis models in the literature have been direc
ted just to predict an impact of a specific scenario. Therefore, our main goal in this approach is to enhance what-if analysis to suggest the best scenarios, in addition to predict their impacts.
Affordable offers are one of the best ways to increase the revenue in telecom companies. Decision makers can predict a potential revenue before launching an offer, depending on what-if analysis system.
This research depends on enhanced k-means algorithm to categorize customers into segments of the same behavior or usage.
he problem with study of the ways of multiple regression analysis is related to
e to the understanding and the explanation of the complicated relations among
variables which affect the studied phenomenon and the huge amount of the
used data in par
ticular some of this outliers.
In this research we have studied and treated the outliers in case of having two
or more non-significant parameter and we have made anew algorithm to solve
the phenomenon outliers on the one hand and solving the problem of the
significant of multiple regression.
