We present a system for regression using MLP neural networks with hyperbolic tangent functions in the input, hidden and output layer. The activation functions in the input and outp...
This article complements the paper [7], where we showed that a compact feasible set of a standard semi-infinite optimization problem can be approximated arbitrarily well by a leve...
In many design tasks it is difficult to explicitly define an objective function. This paper uses machine learning to derive an objective in a feature space based on selected examp...
Estimation of distribution algorithms (EDAs) try to solve an optimization problem by finding a probability distribution focussed around its optima. For this purpose they conduct ...
Encapsulation of states in object-oriented programs hinders the search for test data using evolutionary testing. As client code is oblivious to the internal state of a server obje...