PSO/ACO Algorithm-based Risk Assessment of Human Neural Tube Defects in Heshun County, China
文献类型：SCI/SSCI论文
| 作者 | Liao Y. L. ; Wang J. F. ; Wu J. L. ; Wang J. J. ; Zheng X. Y. |
| 发表日期 | 2012 |
| 关键词 | Neural tube birth defects GIS PSO/ACO algorithm Hierarchical classification Risk map birth-defects shanxi province high-prevalence population |
| 英文摘要 | Objective To develop a new technique for assessing the risk of birth defects, which are a major cause of infant mortality and disability in many parts of the world. Methods The region of interest in this study was Heshun County, the county in China with the highest rate of neural tube defects (NTDs). A hybrid particle swarm optimization/ant colony optimization (PSO/ACO) algorithm was used to quantify the probability of NTDs occurring at villages with no births. The hybrid PSO/ACO algorithm is a form of artificial intelligence adapted for hierarchical classification. It is a powerful technique for modeling complex problems involving impacts of causes. Results The algorithm was easy to apply, with the accuracy of the results being 69.5% +/- 7.02% at the 95% confidence level. Conclusion The proposed method is simple to apply, has acceptable fault tolerance, and greatly enhances the accuracy of calculations. |
| 出处 | Biomedical and Environmental Sciences |
| 卷 | 25 |
| 期 | 5 |
| 页 | 569-576 |
| 收录类别 | SCI |
| 语种 | 英语 |
| ISSN号 | 0895-3988 |
| 源URL | [http://ir.igsnrr.ac.cn/handle/311030/30822]  |
| 专题 | 地理科学与资源研究所_历年回溯文献 |
| 推荐引用方式 GB/T 7714 | Liao Y. L.,Wang J. F.,Wu J. L.,et al. PSO/ACO Algorithm-based Risk Assessment of Human Neural Tube Defects in Heshun County, China. 2012. |
入库方式： OAI收割
来源：地理科学与资源研究所
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