摘要
针对数字海图的成图质量评价问题,提出一种模糊聚类和模糊模式识别相结合的数字海图质量评价算法。算法用于近似处理海图空间数据挖掘的模糊不确定性,减少不确定性对挖掘效果的影响。实例分析结果表明,本算法不仅能够有效地降低海图空间数据挖掘的不确定性,而且能够客观地对数字化作业员的成图质量进行评价,因此有良好的应用价值。
This paper aims at the chart quality evaluation of digital chart, proposes a method for digit- al chart quality assessment based on fuzzy clustering and fuzzy model discrimination. The function of this algorithm is approximately dealing with the fuzzy uncertainty of spatial data mining, reducing the influ- ence of uncertainty to mining outcomes. The result and analysis of example show the algorithm proposed is not only effective to reduce the uncertainty of spatial data mining, hut also can evaluate chart quality from digital working persons. The method should be very valuable.
出处
《测绘科学》
CSCD
北大核心
2016年第11期104-107,123,共5页
Science of Surveying and Mapping
关键词
数字海图
模糊聚类
模糊模式识别
质量评价
digital chart
fuzzy clustering
fuzzy model discrimination
quality assessment