Journal of Applied Science and Engineering

Published by Tamkang University Press

1.30

Impact Factor

2.10

CiteScore

Jingwei Song1,2, Ying Liao1,2, Jiaying He3, Jia Yang4 and Bo Xiang This email address is being protected from spambots. You need JavaScript enabled to view it.1,2

1Key Laboratory of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, P.R. China
2Graduate School, Chinese Academy of Sciences, Beijing 100049, P.R. China
3Center for Geospatial Research, Department of Geography, The University of Georgia, Athens, GA 30602, United States
4College of Territorial Resources and Tourism, Anhui Normal University, Wuhu 241002, P.R. China


 

Received: November 26, 2013
Accepted: May 15, 2014
Publication Date: June 1, 2014

Download Citation: ||https://doi.org/10.6180/jase.2014.17.2.09  


ABSTRACT


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.


Keywords: Solid Waste Planning, Solid Waste Generation, Spatial Clustering, Non-Linear Dynamic System, Data Mining


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