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| Content Provider | Springer Nature Link |
|---|---|
| Author | Jiejun, Huang Xiaorong, He Youchuan, Wan |
| Copyright Year | 2006 |
| Abstract | Bayesian network has a powerful ability for reasoning and semantic representation, which combined with qualitative analysis and quantitative analysis, with prior knowledge and observed data, and provides an effective way to deal with prediction, classification and clustering. Firstly, this paper presented an overview of Bayesian network and its characteristics, and discussed how to lean a Bayesian network structure from given data, and then constructed a Bayesian network model for land resource evaluation with expert knowledge and the dataset. The experimental results based on the test dataset are that evaluation accuracy is 87.5%, and Kappa index is 0.826. All these prove the method is feasible and efficient, and indicate that Bayesian network is a promising approach for land resource evaluation. |
| Starting Page | 1041 |
| Ending Page | 1045 |
| Page Count | 5 |
| File Format | |
| ISSN | 10071202 |
| Journal | Wuhan University Journal of Natural Sciences |
| Volume Number | 11 |
| Issue Number | 4 |
| e-ISSN | 19934998 |
| Language | English |
| Publisher | Wuhan University |
| Publisher Date | 2006-01-01 |
| Publisher Place | Wuhan |
| Access Restriction | Subscribed |
| Subject Keyword | Bayesian networks data mining land resource evaluation models Mathematics Computer Science Physics Life Sciences |
| Content Type | Text |
| Resource Type | Article |
| Subject | Multidisciplinary |
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