In this report, we will be interested at Dynamic Bayesian Network (DBNs) as a model that tries to incorporate temporal dimension with uncertainty. We start with basics of DBN where we especially focus in Inference and Learning concepts and algorithms. Then we will present different levels and methods of creating DBNs as well as approaches of incorporating temporal dimension in static Bayesian network.
%0 Journal Article
%1 IJACSA.2011.020708
%A Nabil Ghanmi Mohamed Ali Mahjoub, Najoua Essoukri Ben Amara
%D 2011
%J International Journal of Advanced Computer Science and Applications(IJACSA)
%K Algorithm; DAG; DBN; EM HMM; HMMs. Inference; Learning; MLE; SEM; coupled
%N 7
%T Characterization of Dynamic Bayesian Network-The Dynamic Bayesian Network as temporal network
%U http://ijacsa.thesai.org/
%V 2
%X In this report, we will be interested at Dynamic Bayesian Network (DBNs) as a model that tries to incorporate temporal dimension with uncertainty. We start with basics of DBN where we especially focus in Inference and Learning concepts and algorithms. Then we will present different levels and methods of creating DBNs as well as approaches of incorporating temporal dimension in static Bayesian network.
@article{IJACSA.2011.020708,
abstract = { In this report, we will be interested at Dynamic Bayesian Network (DBNs) as a model that tries to incorporate temporal dimension with uncertainty. We start with basics of DBN where we especially focus in Inference and Learning concepts and algorithms. Then we will present different levels and methods of creating DBNs as well as approaches of incorporating temporal dimension in static Bayesian network.},
added-at = {2014-02-21T08:00:08.000+0100},
author = {{Nabil Ghanmi Mohamed Ali Mahjoub}, Najoua Essoukri Ben Amara},
biburl = {https://www.bibsonomy.org/bibtex/24f5ce4ae7ad5c2ae52925323ceac5d35/thesaiorg},
interhash = {c2e9ced4261af83ab4f4655cfa588014},
intrahash = {4f5ce4ae7ad5c2ae52925323ceac5d35},
journal = {International Journal of Advanced Computer Science and Applications(IJACSA)},
keywords = {Algorithm; DAG; DBN; EM HMM; HMMs. Inference; Learning; MLE; SEM; coupled},
number = 7,
timestamp = {2014-02-21T08:00:08.000+0100},
title = {{Characterization of Dynamic Bayesian Network-The Dynamic Bayesian Network as temporal network}},
url = {http://ijacsa.thesai.org/},
volume = 2,
year = 2011
}