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Artificial neural network and multiple regression approaches were used to model the cutting forces on the basis of cutting parameters.
Artificial neural networks (ANN) and multiple regression approaches are used to model the surface roughness of AISI 1040 steel.
These properties of genetic data mean that traditional multiple regression approaches cannot be applied.
21 Multiple regression approaches were used to identify factors associated with intention to attend a hypothetical eye health test.
To distinguish associated variables having an indirect influence on WC from participants exerting a more direct influence, two multiple regression approaches were taken.
Path models allow a deeper understanding of data structure than traditional multiple regression approaches, as they permit identification of both direct effects between indicator and response variables and indirect effects that act through mediating variables.
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The authors attempted to control for this alternative interpretation with a multiple regression approach.
These methods used either a multiple regression approach with different bones measurements or a simple regression logistic [28].
The relationship between the ex ante criteria and the three LC indicators was analyzed using a multiple regression approach.
Equation 1 was fitted to experimental data by using a statistical multiple regression approach called method of least square (MLS), which generates the lowest possible residual [38].
For both models, a multiple regression approach was taken to predict Hm from age, Site Index, environmental data and RapidEye spectra and indices.
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