In this paper, we present an application of neural networks in the renewable energy domain. We have developed a methodology for the daily prediction of global solar radiation on a ...
Christophe Paoli, Cyril Voyant, Marc Muselli, Mari...
: Much of the current theory of networked control systems uses simple point-to-point communiodels as an abstraction of the underlying network. As a result, the controller has very ...
Phoebus Chen, Chithrupa Ramesh, Karl Henrik Johans...
This work proposes a novel practical and general-purpose lossless compression algorithm named Neural Markovian Predictive Compression (NMPC), based on a novel combination of Bayesi...
We present an approach to keyhole plan recognition which uses a dynamic belief (Bayesian) network to represent features of the domain that are needed to identify users’ plans and...
David W. Albrecht, Ingrid Zukerman, Ann E. Nichols...
BAYDA is a software package for flexible data analysis in predictive data mining tasks. The mathematical model underlying the program is based on a simple Bayesian network, the Na...