  This paper investigates the use of artificial neural networks (ANNs) to solve
differential equations (DEs) and the construction of the loss function which
meets both differential equation and its initial/boundary condition of a
certain DE. In section 2, the loss function is generalized to $n^\text{th}$
order ordinary differential equation(ODE). Other methods of construction are
examined in Section 3 and applied to three different models to assess their
effectiveness.
