Next Generation Artificial Neural Networks for Civil Engineering
Ian Flood · Journal of Computing in Civil Engineering · 2006
If we measure complexity in these simple terms as the number of primary processing units that can be employed usefully in an application then we can compare today’s general purpose digital computer to the brain of a rabbit comprising in the order of 10 9 neurons, while artificial neural networks have progressed no further than the brain of the humble nematode comprising just 302 neurons. Obviously the number of primary processing units that can be employed usefully in a given application provides a very simplified means of comparing complexity—an artificial neuron is usually a much more complicated processing device than a transistor and, moreover, it is likely that significant aspects of the computational mechanisms underlying biological neural networks are yet to be discovered and could be dependent on processes that operate at a lower level than individual neurons see Bullock 2005 for example. Nevertheless, the comparison clearly demonstrates that a plateau has been reached in the development of this technology and that this plateau is at a low elevation.