[图书][B] Bayesian networks: an introduction
T Koski, J Noble - 2011 - books.google.com
Bayesian Networks: An Introduction provides a self-contained introduction to the theory and
applications of Bayesian networks, a topic of interest and importance for statisticians …
applications of Bayesian networks, a topic of interest and importance for statisticians …
Complex system reliability modelling with dynamic object oriented Bayesian networks (DOOBN)
Nowadays, the complex manufacturing processes have to be dynamically modelled and
controlled to optimise the diagnosis and the maintenance policies. This article presents a …
controlled to optimise the diagnosis and the maintenance policies. This article presents a …
Bayesian networks inference algorithm to implement Dempster Shafer theory in reliability analysis
This paper deals with the use of Bayesian networks to compute system reliability. The
reliability analysis problem is described and the usual methods for quantitative reliability …
reliability analysis problem is described and the usual methods for quantitative reliability …
BayesOWL: Uncertainty modeling in semantic web ontologies
Z Ding, Y Peng, R Pan - Soft computing in ontologies and semantic web, 2006 - Springer
It is always essential but difficult to capture incomplete, partial or uncertain knowledge when
using ontologies to conceptualize an application domain or to achieve semantic …
using ontologies to conceptualize an application domain or to achieve semantic …
A Bayesian network approach to ontology mapping
R Pan, Z Ding, Y Yu, Y Peng - The Semantic Web–ISWC 2005: 4th …, 2005 - Springer
This paper presents our ongoing effort on developing a principled methodology for
automatic ontology mapping based on BayesOWL, a probabilistic framework we developed …
automatic ontology mapping based on BayesOWL, a probabilistic framework we developed …
Reliability modelling with dynamic bayesian networks
Nowadays, the complex manufacturing processes have to be dynamically modelled and
controlled to optimise the diagnosis and the maintenance strategies. The work reported here …
controlled to optimise the diagnosis and the maintenance strategies. The work reported here …
An explication of uncertain evidence in Bayesian networks: Likelihood evidence and probabilistic evidence: Uncertain evidence in Bayesian networks
This paper proposes a systematized presentation and a terminology for observations in a
Bayesian network. It focuses on the three main concepts of uncertain evidence, namely …
Bayesian network. It focuses on the three main concepts of uncertain evidence, namely …
Expert system for medicine diagnosis using software agents
O Arsene, I Dumitrache, I Mihu - Expert Systems with Applications, 2015 - Elsevier
In order to simplify the information exchange within the medical diagnosis process, a
collaborative software agents framework is presented. The human body systems (eg …
collaborative software agents framework is presented. The human body systems (eg …
Bayesian network reasoning with uncertain evidences
Y Peng, S Zhang, R Pan - International Journal of Uncertainty …, 2010 - World Scientific
This paper investigates the problem of belief update in Bayesian networks (BN) with
uncertain evidence. Two types of uncertain evidences are identified: virtual evidence …
uncertain evidence. Two types of uncertain evidences are identified: virtual evidence …
The logical essentials of Bayesian reasoning
B Jacobs, F Zanasi - Foundations of probabilistic programming, 2020 - books.google.com
This chapter offers an accessible introduction to the channel-based approach to Bayesian
probability theory. This framework rests on algebraic and logical foundations, inspired by the …
probability theory. This framework rests on algebraic and logical foundations, inspired by the …