Artificial neural networks in the nuclear engineering (Part 1)

Artificial Neural Networks (ANN) can be defined as 'parallel systems composed of layers of simple processing units highly interconnected and inspired in the human brain.' ANN can be used to solve problems of difficult modeling, when the data are fail or incomplete and in problems of control of high complexity. Several problems related with network training and generalization are to be solved to a safe utilization in nuclear plants systems. This work, divided into two parts, intends to begin a discussion on three ANN concepts: feed-forward neural networks, Self-Organized Maps (SOM), and multi-synaptic neural networks. The discussion will cover control applications, approximation of functions and pattern recognition. A few set of samples are commented. This first part focus on feed-forward neural networks with the back-propagation algorithm. (author)