Abstract. Interval analysis is a powerful tool which allows to design branch-and-bound algorithms able to solve many global optimization problems. In this paper we present new adap...
Obtaining a bayesian network from data is a learning process that is divided in two steps: structural learning and parametric learning. In this paper, we define an automatic learni...
Different schemes for large scale networks hosting distributed applications have been recently adopted for network path marking based on adaptive behavior of swarm-based agents. T...
Radial basis function network (RBF) kernels are widely used for support vector machines (SVMs). But for model selection of an SVM, we need to optimize the kernel parameter and the ...
Wind energy has an increasing influence on the energy supply in many countries, but in contrast to conventional power plants it is a fluctuating energy source. For its integration...