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The results of many measured engineering experiments require an analysis and study process in order to determine the relationships between the independent variables and the dependent variables, and accordingly, the accuracy of the values of the adopted variables becomes an urgent necessity. In this research paper we will take a sample of laboratory data and find the necessary relationships between the different variables, and then we will present some models of artificial neural networks to find solutions to these relationships in order to make the necessary comparisons to reach some of the necessary recommendations regarding the handling of measured data.

Analysis of Methods used to Investigate Engineering Measured Experimental Data