Computer Science ›› 2018, Vol. 45 ›› Issue (12): 262-267,287.doi: 10.11896/j.issn.1002-137X.2018.12.043

• Graphics, Image & Pattern Recognition • Previous Articles     Next Articles

Visual Analysis Method of Garbage Disposal Modes Based on Self-organizing Maps Clustering

QIN Xu-jia, SHAN Yang-yang, XU Fei, ZHENG Hong-bo, ZHANG Mei-yu   

  1. (School of Computer Science and Technology,Zhejiang University of Technology,Hangzhou 310023,China)
  • Received:2017-06-27 Online:2018-12-15 Published:2019-02-25

Abstract: A hybrid visual analysis method was proposed for the data of garbage disposal modes in various provinces of China.In order to analyze the data from multiple views,this paper combined three visualization techniques including unified distance matrix,parallel coordinate and Small-Multiple,designed and realized the interactions among the three views.Firstly,the data are processed by clustering so that the garbage disposal modes of different provinces in recent years can be divided into different categories.The clustering used in this paper is based on self-organizing maps (SOM) neural network clustering algorithm.Secondly,according to the results of SOM clustering,the unified distance matrix is used for visualization,and the parallel coordinate is used to describe the attributes of each clustering result.In order to analyze the geographical and sequential attributes of data,the Small-Multiple visualization technology is used.Thirdly,interactions such as multi-view linkage and refreshing are implemented to help users explore the data on their own and achieve interactive display and analysis of multiple views.The experimental results show that the hybrid visualization method can achieve a good visualization effect of multi-attributes interaction and can help users to understand the distribution and trend analysis of garbage disposal modes in China.

Key words: Visualization, SOM clustering, Unified distance matrix, Parallel coordinate, Small-Multiple

CLC Number: 

  • TP391
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