Analyzing Complexity of Municipal Solid Waste Stations Using Approximate Entropy and Spatial Clustering

被引：0

作者：

Song, Jingwei ^{[1
,2
]}

Liao, Ying ^{[1
,2
]}

He, Jiaying ^{[3
]}

Yang, Jia ^{[4
]}

Xiang, Bo ^{[1
,2
]}

机构：

[1] Chinese Acad Sci, Inst Remote Sensing & Digital Earth, Key Lab Digital Earth Sci, Beijing 100094, Peoples R China

[2] Chinese Acad Sci, Grad Sch, Beijing 100049, Peoples R China

[3] Univ Georgia, Ctr Geospatial Res, Dept Geog, Athens, GA 30602 USA

[4] Anhui Normal Univ, Coll Territorial Resources & Tourism, Wuhu 241002, Peoples R China

来源：

JOURNAL OF APPLIED SCIENCE AND ENGINEERING | 2014年 / 17卷 / 02期

关键词：

Solid Waste Planning; Solid Waste Generation; Spatial Clustering; Non-Linear Dynamic System; Data Mining;

D O I：

10.6180/jase.2014.17.2.09

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

The generation of municipal solid waste (take MSW for short hereafter) is a deterministic process with chaotic behaviors, which is highly sensitive to initial conditions. In this paper, we propose the approximate entropy (ApEn) to measure the spatial distribution of the MSW stations. We also provide the k-means spatial clustering method to investigate the spatial heterogeneity and homogeneity. Results show that MSW stations have spatial correlations and they can be divided into separate groups by spatial clustering method for further study and prediction.

引用

页码：185 / 192

页数：8

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