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基于XML树图差异度算法的青蒿鉴定
引用本文:余锡鹏,初依侬,程红艳,李庚,梁志伟.基于XML树图差异度算法的青蒿鉴定[J].中国实验方剂学杂志,2019,25(21):182-188.
作者姓名:余锡鹏  初依侬  程红艳  李庚  梁志伟
作者单位:广州中医药大学 中医药数理工程研究院, 广州 510006,东莞广州中医药大学中医药数理工程研究院, 广东 东莞 523808,广州中医药大学 中医药数理工程研究院, 广州 510006,广州中医药大学 中医药数理工程研究院, 广州 510006,广州中医药大学 中医药数理工程研究院, 广州 510006;东莞广州中医药大学中医药数理工程研究院, 广东 东莞 523808
基金项目:国家高技术研究发展计划(863计划)项目(2013AA020418);广东省科学技术厅重大专项(2012A080205001)
摘    要:目的:研究并创建可扩展标记语言(XML)树图差异度算法,为中药青蒿鉴定研究提供新工具。方法:结合文献研究筛选中药青蒿"宏观、中观、微观"(简称"宏、中、微")等关键信息。在关键信息的基础上,引采国内外专业领域相关上位标准,为每个数据元分配与语言无关的唯一标识,建立相关数据元编码规则。将数字化编码技术应用在弹性结构编辑器上,创建返回格式为第5版超文本标记语言(HTML5)或XML树图。在差异度相关算法的基础上,创新研制同时兼顾拓扑和语义的中药青蒿XML树图差异度算法,并建立青蒿相关数学函数表达模型,通过计算结果与现实实际的对比,不断调试算法模型,直至核涵算法模型收敛。结果:通过对差异度算法研究可对XML树图进行两两间差异度比较计算,最终优化确立中药青蒿的鉴定模型,经测试树图计算分析该模型有效率达100%。结论:创建的XML树图差异度算法能够有效辅助鉴定中药青蒿,为中药领域智能化应用研究的开展提供了一定的技术支撑与理论指导。

关 键 词:青蒿  可扩展标记语言  树图结构  差异度  药材鉴定  方法学研究  数字化
收稿时间:2018/12/12 0:00:00

Identification of Artemisiae Annuae Herba Based on Algorithm for Diversity of XML Tree Map
YU Xi-peng,CHU Yi-nong,CHENG Hong-yan,LI Geng and LIANG Zhi-wei.Identification of Artemisiae Annuae Herba Based on Algorithm for Diversity of XML Tree Map[J].China Journal of Experimental Traditional Medical Formulae,2019,25(21):182-188.
Authors:YU Xi-peng  CHU Yi-nong  CHENG Hong-yan  LI Geng and LIANG Zhi-wei
Institution:Mathematical Engineering Academy of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China,Dongguan and Guangzhou University of Chinese Medicine Cooperative Academy of Mathematical and Engineering for Chinese Medicine, Dongguan 523808, China,Mathematical Engineering Academy of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China,Mathematical Engineering Academy of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China and Mathematical Engineering Academy of Chinese Medicine, Guangzhou University of Chinese Medicine, Guangzhou 510006, China;Dongguan and Guangzhou University of Chinese Medicine Cooperative Academy of Mathematical and Engineering for Chinese Medicine, Dongguan 523808, China
Abstract:Objective: To study and create the algorithm for the diversity (AD) of extensible markup language (XML) tree map, and provide a new tool for the identification of Artemisiae Annuae Herba. Method: According to the literature research, the key information of Artemisiae Annuae Herba was selected from the macroscopic, mesoscopic and microscopic information, etc. Based on the key information, the relevant upper standards of domestic and foreign professional fields were cited to assign the unique identification independent of language for each data element, and the coding rules of relevant data elements were established. The digital coding technology was applied to the flexible structure editor, and the tree map was created, which could be returned as the 5th version of hypertext markup language (HTML5) or XML format. Based on the diversity related algorithms, the authors innovatively developed the AD of XML tree map of Artemisiae Annuae Herba, which took into account both of topology and semantics, and the expression model of related mathematical functions of Artemisiae Annuae Herba was established. By comparing the calculation results with the reality, the algorithm model was debugged continuously until the convergence of the core-culvert algorithm model. Result: Through the research on AD, the diversity between two XML tree maps could be calculated, and the discrimination or identification model of Artemisiae Annuae Herba also could be finally optimized and established. After calculation and analysis of the tested tree maps, the effective rate of the model was 100%. Conclusion: In this study, the establishment of the AD of XML tree map can effectively assist in the identification of Artemisiae Annuae Herba, which provides certain technical support and theoretical guidance for the research on intelligent application of traditional Chinese medicine.
Keywords:Artemisiae Annuae Herba  extensible markup language  tree map structure  diversity  identification of medicinal materials  methodological research  digitization
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