Data-Defined Problems and Multiversion Neural-Net Systems

Autor: Partridge, Derek, Yates, William Β

Publikováno v: Journal of Intelligent Systems, Vol 7, Iss 1-2, Pp 19-32 (1997)

Externí odkaz: https://doaj.org/article/15c36da3ae7644e49f166a18fd6dfffb

A Bayesian Methodology for Estimating Uncertainty of Decisions in Safety-Critical Systems

Autor: Schetinin, Vitaly, Fieldsend, Jonathan, Partridge, Derek, Krzanowski, Wojtek, Everson, Richard, Bailey, Trevor, Hernandez, Adolfo

Publikováno v: Frontiers in Artificial Intelligence and Applications. Volume 149, IOS Press Book, 2006. Integrated Intelligent Systems for Engineering Design. Edited by Xuan F. Zha, R.J. Howlett. ISBN 978-1-58603-675-1, pp. 82-96

Uncertainty of decisions in safety-critical engineering applications can be estimated on the basis of the Bayesian Markov Chain Monte Carlo (MCMC) technique of averaging over decision models. The use of decision tree (DT) models assists experts to in

Externí odkaz: http://arxiv.org/abs/1012.0322

Comparison of the Bayesian and Randomised Decision Tree Ensembles within an Uncertainty Envelope Technique

Autor: Schetinin, Vitaly, Fieldsend, Jonathan E., Partridge, Derek, Krzanowski, Wojtek J., Everson, Richard M., Bailey, Trevor C., Hernandez, Adolfo

Publikováno v: Journal of Mathematical Modelling and Algorithms, 2005

Multiple Classifier Systems (MCSs) allow evaluation of the uncertainty of classification outcomes that is of crucial importance for safety critical applications. The uncertainty of classification is determined by a trade-off between the amount of dat

Externí odkaz: http://arxiv.org/abs/cs/0504066

Tento výsledek nelze pro nepřihlášené uživatele zobrazit.
K zobrazení výsledku je třeba se přihlásit.

Heuristic methods in the analysis of program statements

Autor: Partridge, Derek

Externí odkaz: http://ethos.bl.uk/OrderDetails.do?uin=uk.bl.ethos.643758