Neural networks - computational models loosely inspired by the brain - are now finding widespread application for solving classification, function approximation and optimization problems. This paper provides a brief but comprehensive review of neural networks. Various learning paradigms are discussed, as is the use of neural networks of solving optimization problems. We also describe briefly an approach to optimizing neural network applications using the genetic algorithm.
|Original language||English (US)|
|Number of pages||5|
|Journal||Proceedings of the American Power Conference|
|Issue number||pt 2|
|State||Published - Jan 1 1991|
|Event||Proceedings of the 53rd Annual Meeting of the American Power Conference - Chicago, IL, USA|
Duration: Apr 29 1991 → May 1 1991