Title :
Pattern Recognition for Ship Based on Bayesian Networks
Author :
Wang, QingJiang ; Gao, Xiaoguang ; Chen, DaQing
Author_Institution :
Northwestern Polytech. Univ., Xi´´an
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.
Keywords :
belief networks; pattern recognition; ships; Bayesian networks; directed acyclic graph; pattern recognition; ship; Bayesian methods; Data mining; Equations; Graphical models; Machine learning; Machine learning algorithms; Marine vehicles; Niobium; Pattern recognition; Probability;
Conference_Titel :
Fuzzy Systems and Knowledge Discovery, 2007. FSKD 2007. Fourth International Conference on
Conference_Location :
Haikou
Print_ISBN :
978-0-7695-2874-8
DOI :
10.1109/FSKD.2007.447
