A SOTER (soil and terrain digital database) project at the scale of 1:500000 has been tested using the CIS (geographical information system) methodology in Hainan Province of tropical China. Soil and terrain map units...A SOTER (soil and terrain digital database) project at the scale of 1:500000 has been tested using the CIS (geographical information system) methodology in Hainan Province of tropical China. Soil and terrain map units were delineated by SOTER manual. An ARC/ INFO GIS software has been used for geometric data storing and map editing, with attribute data stored in a relational database management system, dBASEIII PLUS.展开更多
Interval-valued data appear as a way to represent the uncertainty affecting the observed values. Dealing with interval-valued information systems is helpful to generalize the applications of rough set theory. Attribut...Interval-valued data appear as a way to represent the uncertainty affecting the observed values. Dealing with interval-valued information systems is helpful to generalize the applications of rough set theory. Attribute reduction is a key issue in analysis of interval-valued data. Existing attribute reduction methods for single-valued data are unsuitable for interval-valued data. So far, there have been few studies on attribute reduction methods for interval-valued data. In this paper, we propose a framework for attribute reduction in interval-valued data from the viewpoint of information theory. Some information theory concepts, including entropy, conditional entropy, and joint entropy, are given in interval-valued information systems. Based on these concepts, we provide an information theory view for attribute reduction in interval-valued information systems. Consequently, attribute reduction algorithms are proposed. Experiments show that the proposed framework is effective for attribute reduction in interval-valued information systems.展开更多
基金Project supported by the National Natural Science Foundation of Chinathe Foundation of Chinese Academy of Sciences.
文摘A SOTER (soil and terrain digital database) project at the scale of 1:500000 has been tested using the CIS (geographical information system) methodology in Hainan Province of tropical China. Soil and terrain map units were delineated by SOTER manual. An ARC/ INFO GIS software has been used for geometric data storing and map editing, with attribute data stored in a relational database management system, dBASEIII PLUS.
基金Project supported by the National Natural Science Foundation of China(Nos.61473259,61502335,61070074,and60703038)the Zhejiang Provincial Natural Science Foundation(No.Y14F020118)the PEIYANG Young Scholars Program of Tianjin University,China(No.2016XRX-0001)
文摘Interval-valued data appear as a way to represent the uncertainty affecting the observed values. Dealing with interval-valued information systems is helpful to generalize the applications of rough set theory. Attribute reduction is a key issue in analysis of interval-valued data. Existing attribute reduction methods for single-valued data are unsuitable for interval-valued data. So far, there have been few studies on attribute reduction methods for interval-valued data. In this paper, we propose a framework for attribute reduction in interval-valued data from the viewpoint of information theory. Some information theory concepts, including entropy, conditional entropy, and joint entropy, are given in interval-valued information systems. Based on these concepts, we provide an information theory view for attribute reduction in interval-valued information systems. Consequently, attribute reduction algorithms are proposed. Experiments show that the proposed framework is effective for attribute reduction in interval-valued information systems.
