Recurrent neural networks serve as black-box models for nonlinear dynamical systems identification and time series prediction. Training of recurrent networks typically minimizes t...
Cyber-physical systems increasingly rely on dynamically adaptive programs to respond to changes in their physical environment; examples include ecosystem monitoring and disaster r...
Abstract. Accurate and fine-grained prediction of future user location and geographical profile has interesting and promising applications including targeted content service, adv...
We introduce a stochastic model that describes the quasistatic dynamics of an electric transmission network under perturbations introduced by random load fluctuations, random rem...
Marian Anghel, Kenneth A. Werley, Adilson E. Motte...
d Abstract) Jane Hillston Laboratory for Foundations of Computer Science, The University of Edinburgh, Scotland Quantitative Analysis Stochastic process algebras extend classical p...