Differentiation of syndromes with SVM
文献类型:期刊论文
作者 | Sun, Zhanquan; Xi, Guangcheng![]() ![]() |
刊名 | ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS
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出版日期 | 2006 |
卷号 | 3973页码:786-791 |
英文摘要 | Differentiation of syndromes is the kernel theory of Traditional Chinese Medicine (TCM). How to diagnose syndromes correctly with scientific means according to symptoms is the first problem in TCM. Several modem approaches have been applied, but no satisfied results have been obtained because of the complexity of diagnosis procedure. Support Vector Machine (SVM) is a new classification technique and has drawn much attention on this topic in recent years. In this paper, we combine non-linear Principle Component Analysis (PCA) neural network with multi-class SVM to realize differentiation of syndromes. Non-linear PCA is used to preprocess clinical data to save computational cost and reduce noise. The multi-class SVM takes the non-linear principle components as its inputs and determines a corresponding syndrome. Analyzing of a TCM example shows its effectiveness. |
WOS标题词 | Science & Technology ; Technology |
类目[WOS] | Computer Science, Artificial Intelligence ; Computer Science, Theory & Methods |
研究领域[WOS] | Computer Science |
关键词[WOS] | MULTIOBJECTIVE OPTIMIZATION ; RELIABILITY |
收录类别 | ISTP ; SCI |
语种 | 英语 |
WOS记录号 | WOS:000239485300115 |
源URL | [http://ir.ia.ac.cn/handle/173211/9327] ![]() |
专题 | 自动化研究所_09年以前成果 |
作者单位 | Chinese Acad Sci, Inst Automat, Key Lab Complex Syst & Intelligence Sci, Beijing 100080, Peoples R China |
推荐引用方式 GB/T 7714 | Sun, Zhanquan,Xi, Guangcheng,Yi, Jianqiang,et al. Differentiation of syndromes with SVM[J]. ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS,2006,3973:786-791. |
APA | Sun, Zhanquan.,Xi, Guangcheng.,Yi, Jianqiang.,Wang, J.,Yi, Z.,...&Yin, H.(2006).Differentiation of syndromes with SVM.ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS,3973,786-791. |
MLA | Sun, Zhanquan,et al."Differentiation of syndromes with SVM".ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 3, PROCEEDINGS 3973(2006):786-791. |
入库方式: OAI收割
来源:自动化研究所
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