Hybrid systems are dynamical systems with the ability to describe mixed discretecontinuous evolution of a wide range of systems. Consequently, at first glance, hybrid systems appe...
Alberto Casagrande, Carla Piazza, Alberto Policrit...
A hybrid Bayesian Network (BN) is one that incorporates both discrete and continuous nodes. In our extensive applications of BNs for system dependability assessment the models are...
Martin Neil, Manesh Tailor, Norman E. Fenton, Davi...
Abstract. Motivated by three applications which are under investigation at the Honeywell Research Laboratory in Minneapolis, we introduce a class of large scale control problems. I...
In this paper we present a general hybrid systems modeling framework to describe the flow of traffic in communication networks. To characterize network behavior, these models use...
In this paper we propose a Neural Net-PMRS hybrid for forecasting time-series data. The neural network model uses the traditional MLP architecture and backpropagation method of tr...