In this paper, a General Neural Networks Regression (GNNR) is presented. The position analysis of multi-link five-point suspension system is solved using GNNR. The mechanism of wheel suspension is a multi-body system (MBS) which is a system of bodies (in this case rigid links of given length) whose mutual position is bounded by geometrical constraints (joints) and by active kinematical driving constraints in the form of prescribed motion related to the degrees-of-freedom (DOF) of the given mechanism. GNNR is first trained with coordinates of the defined points and input driving variables. After training, performance is measured by having the network generate the coordinates of the defined points in terms of driving input variables. It is found that GNNR provides a simple and effective way to model the spatial kinematics of the five point's suspension and eliminate the convergence problems associated with algorithmic solution methods.
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