Pattern recognition for ship based on bayesian networks

Qingjiang Wang, Xiaoguang Gao, Daqing Chen

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

15 Scopus citations

Abstract

Bayesian networks (BNs) are a powerful tool for pattern recognition. A BNs has two parts: parameters and structure composed of a directed acyclic graph (DAG) with some nodes. Then, according to the target feature, an approach based on BNs for pattern recognition is presented and the step of the approach is presented: constructing its nodes, modifying the node's states and distributing the node's probability. The process using the approach for pattern recognition is showed by an experiment, and the empirical results provide evidences that the approach is reasonable and effective.

Original languageEnglish
Title of host publicationProceedings - Fourth International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007
Pages684-688
Number of pages5
DOIs
StatePublished - 2007
Event4th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007 - Haikou, China
Duration: 24 Aug 200727 Aug 2007

Publication series

NameProceedings - Fourth International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007
Volume4

Conference

Conference4th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2007
Country/TerritoryChina
CityHaikou
Period24/08/0727/08/07

Keywords

  • Bayesian networks
  • Conditional independence
  • Pattern recognition
  • Target feature

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