模糊聚类和模糊模式识别的海图质量评价算法  

Digital chart quality assessment based on fuzzy clustering and fuzzy model discrimination

作　　者：陈永昌[1] 宋国大[1] 靳军[2] 

机构地区：[1]海军出版社,天津300450 [2]大连舰艇学院海洋测绘系,辽宁大连116018

出　　处：《测绘科学》2016年第11期104-107,123,共5页Science of Surveying and Mapping

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.

关 键 词：数字海图 模糊聚类 模糊模式识别 质量评价 

分 类 号：P229[天文地球—大地测量学与测量工程]