Automatic Generation of Neural Network Architecture Using Evolutionary Computation
Erwin Vonk, Lakhmi C. Jain, R.P. Johnson · Advances in fuzzy systems · 1997
computation, genetic algorithms, genetic programming This paper reports the application of evolutionary computation in the automatic generation of a neural network architecture. It is a usual practice to use trial and error to find a suitable neural network architecture. This is not only time consuming but may not generate an optimal solution for a given problem. The use of evolutionary computation is a step towards automation in neural network architecture generation. In this paper a brief introducuon to the field is given as well as an implementation of automatic neural network generation using genetic programming. 1.