一种基于顶点聚类的线要素简化算法改进
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摘要
首先介绍了一种利用SOM神经网络对顶点进行聚类的线要素简化算法,该算法以线要素各顶点x,y坐标为输入样本集,经过SOM神经网络的训练,形成对原有顶点的聚类,每个聚类保留一个顶点作为简化后的结果。然后分析该算法存在的一些问题,先假设加入角度和距离两维能改善原算法的效果。最后自主实现算法,并采用相关实验数据加以验证,证明增加SOM维数确实行之有效。
Firstly,a linear features simplification algorithm based on vertexs clustering var SOM neural network was introduced.After the SOM neural network was trained by the x,y coordinates of the linear feature's vertexs,the vertexs of the linear feature was clustered by the SOM neurons,one vertex was selected in every cluster to build up the simplified linear feature.Analysising some problems existing in the algorithm,it was assumed that the additional two dimensional,the angle and the distance,can improve the effect of the original algorithm.The algorithm was implemented independently and validated by related experimental data,which shows that our assumption is indeed correct.
Firstly,a linear features simplification algorithm based on vertexs clustering var SOM neural network was introduced.After the SOM neural network was trained by the x,y coordinates of the linear feature's vertexs,the vertexs of the linear feature was clustered by the SOM neurons,one vertex was selected in every cluster to build up the simplified linear feature.Analysising some problems existing in the algorithm,it was assumed that the additional two dimensional,the angle and the distance,can improve the effect of the original algorithm.The algorithm was implemented independently and validated by related experimental data,which shows that our assumption is indeed correct.
引文
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[2]应申,郭仁忠,闫浩文,等.制图综合中等高线相交的判断和消除[J].测绘科学,2001,26(4):39-41.
[3]陈波,朱鲲鹏,薛本新.线状要素化简算法的分析与评估[J].测绘科学技术学报,2007,24(2):121-124.
[4]齐清文.智能化制图综合在GIS环境下的实现方法研究[J].地理科学进展,1998,17(2):15-22.
[5]田震,王家耀,武芳.自动制图综合人工神经元网络方法的研究[J].解放军测绘学院学报,1998,15(4):280-284.
[6]修丽娜,刘湘南.人工神经网络遥感分类方法研究现状及发展趋势探析[J].遥感技术与应用,2003,18(5):339-345.
[7]MCMASTER R B.Automated Line Generalization[J].Cartographica:The International Journal for Geographic Information and Geovisualization,1987,24(2);74-111.
[8]JIANG B,NAKOS B.Line Simplification Using Selforganizing Maps[C/DK]//A Working Paper Presented at ISPRS Workshop on Spatial Analysis and Decision Making.Hong Kong,2003.
[9]DUTTON G.Scale,Sinuosity,and Point Selection in Digital Line Generalization[J].Cartography and Geographic Information Science,1999,26(1):33-54.
[10]焦健,魏立力,曾琪明.基于QTM的线状图形自动化简算法探讨[J].测绘科学,2005,30(5):89-91.
[11]RAPOSO P.Scale-Specific Automated Map Line Simplification by Vertex Clustering on a Hexagonal Tessellation[D].Pennsylvnia.The Pennsylvania State University,2011:l-6.
[12]WANG Z.MULLER J C.Line Generalization Based on Analysis of Shape Characteristics[J].Cartography and Geographic Information Science,1998,25(1):3-15.
[13]郭庆胜,黄远林,章莉萍.曲线的弯曲识别方法研究[J].武汉大学学报:信息科学版,2008,33(6):596-599.
[14]毋河海.数字曲线拐点的自动确定[J].武汉大学学报:信息科学版,2003,28(3):330-335.
[15]MCMASTER R B.A Statistical Analysis of Mathematical Measures for Linear Simplification[J].Cartography and Geographic Information Science,1986,13(2):103-116.