多分类系统类别语义分析——以自然资源调查为例

自然资源调查监测结果的实质融合是构建自然资源统一调查监测体系急需解决的问题。该文从分析多源数据的分类系统语义关系出发,以自然资源调查试点所采用的分类系统为例,研究了其与调查中重点涉及的两个参考底图分类系统之间的类别语义关系。通过构建语义参考概念树,定量计算各分类系统间语义转换度和语义相似度,描述分类系统类别间的单向和双向语义关系,为自然资源分类系统与其他系统之间的数据融合提供依据。实验结果表明,试点自然资源分类系统与土地利用现状分类系统以及地理国情分类系统的语义转换度分别为6715%和7215%。该研究为提高自然资源调查效率、构建统一自然资源本体库提供了支持,为多源数据的实质融合提供了理论依据。

A GIS-based research on the distribution of rural settlements in Yulin of northern Shaanxi

The development and distribution pattern of rural settlements was greatly limited by their natural and social environment. Taking Yulin prefecture in northern Shaanxi抯 Loess Plateau area as an example, 1:250,000 map-scale national geographical database as a major information source, a GIS-based research was conducted to investigate the spatial distribution of the rural settlements. In this paper, many significant characteristics of the rural settlement distribution are reviewed by means of a series of GIS-based information processing methodology. The results obtained in this study should be helpful for the urban and rural settlements reconstruction planning in this area.

Developing a geographic Case-Based Reasoning approach

Case-Based Reasoning （CBR） is an AI approach and been applied to many areas. However, one area - geography - has not been investigated systematically and thus has been identified as the focus for this study. This paper intends to further extend current CBR to a geographic CBR （Geo-CBR）. First, the concept of Geo-CBR is proposed. Second, a representation model for geographic cases has been established based on the Tesseral model and on a further extension in spatio-temporal dimensions for geographic cases. Third, a reasoning model for Geo-CBR is developed by considering the spatio-temporat characteristics and the uncertain and limited information of geographic cases. Finally, the Geo-CBR model is applied to forecasting the production of ocean fisheries to demonstrate the applicability of the developed Geo-CBR in solving problems in the real world. According to the experimental results, Geo-CBR is an effective and easy-to-implement approach for predicting geographic cases quantitatively.

沙芥中含氮类化学成分的分离与鉴定

目的对蒙药沙芥(Pugionium cornutum(L.)Gaertn.)中的含氮类成分进行研究,为其资源开发与利用提供依据。方法综合应用大孔吸附树脂、正相硅胶、反相ODS和Sephadex LH-20等柱色谱以及高效液相色谱法对沙芥中含氮类成分进行分离纯化,并结合单体成分的理化性质与核磁共振波谱数据鉴定其结构。结果从沙芥的体积分数70%乙醇提取物中分离鉴定了10个含氮类成分,分别为5-(methylsulfinyl)-pentanenitrile(1)、2-苯乙基芥子油苷(2)、2-phenylethyl-desulphoglucosinolate(3)、N-methoxyl-3-indolymethyldesulphoglucosinolate(4)、arvelexin(5)、cappariloside A(6)、L-色氨酸(7)、L-苯丙氨酸(8)、3-phenylpropanamide(9)、腺苷(10)。结论在对沙芥化学成分的研究过程中,分离鉴定了10个含氮类单体成分。其中,化合物1~7、9、10为首次从该属植物中分离得到,并首次报道了化合物2的核磁共振波谱数据。