no, i think its more like, you use a neural network when you don't know the fundamental governing equations. you use the network to derive its own governing equations given a certain set of input data. the the netowrk not only has to use the governing equations, it also has to figure out what they are.

in most cases where modeling is too complex or too tough for engineering applications, we know the governing equations. and the governing equations and there application is in and of itself, too complex for computational solutions to be generated in a reasonable time. and thats when you know and understand the system, and why its behaving as it is. if you don't know that, like a neural network wont, then you have added a HUGE mess of computation that your network has to do. it has to figure out what the problem is that it needs to solve. whereas, we already know how to solve the problem.