Title :
A Bayesian Network Based Intelligent Plant Classification System
Author_Institution :
Nanjing Audit Univ., Nanjing, China
Abstract :
We design a convenience way in plant research, which can classify the hibernal plants automatically. Different features related to this model will be taken into consideration, and other influenced facts will be included as well. The main points of the classification should be picked out and we will implement the system according to them and on the basis of Bayes. The Bayes Network is in use of coefficient learning so that we can get the advantages of adaptive learning and the best effects of classification through self-learning and adjusting parameters according to actual data. In this way, the problem of classifying hibernal plant automatically is solved and the result of experiment will be showed in the paper.
Keywords :
belief networks; biology computing; botany; pattern classification; unsupervised learning; Bayes network; Baysian network-based intelligent plant classification system; adaptive learning; automatic hibernal plant classification; coefficient learning; self-learning; Bayes; adaptive learning; plant; plant classification;
Conference_Titel :
Information Science and Engineering (ISISE), 2012 International Symposium on
Conference_Location :
Shanghai
Print_ISBN :
978-1-4673-5680-0
DOI :
10.1109/ISISE.2012.65