Learning Bayesian networks from data is an N-P hard problem with important practical applications. Several researchers have designed algorithms to overcome the computational comple...
Artificial Neural Networks (ANNs) have proved both a popular and powerful technique for pattern recognition tasks in a number of problem domains. However, the adoption of ANNs in ...
This paper presents preliminary work done on simulationbased optimization of a stochastic material-dispatching system in a retailer network. The problem we consider is one of dete...
Abstract. Protein-protein interactions (PPIs) are one of the most important mechanisms in cellular processes. To model protein interaction sites, recent studies have suggested to f...
This paper looks upon the standard genetic algorithm as an artificial self-organizing process. With the purpose to provide concepts that make the algorithm more open for scalabili...