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The Scientific World Journal
Volume 2014, Article ID 834357, 7 pages
http://dx.doi.org/10.1155/2014/834357
Research Article

Simulated Annealing Based Hybrid Forecast for Improving Daily Municipal Solid Waste Generation Prediction

1Key Laboratory of Digital Earth Sciences, Institute of Remote Sensing and Digital Earth, Chinese Academy of Sciences, Beijing 100094, China
2Graduate School, Chinese Academy of Sciences, Beijing 100049, China
3Changjiang River Scientific Research Institute, Wuhan 430010, China
4Center for Geospatial Research, Department of Geography, The University of Georgia, Athens, GA 30602, USA
5School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, China

Received 16 April 2014; Accepted 25 May 2014; Published 30 June 2014

Academic Editor: Guojie Zhang

Copyright © 2014 Jingwei Song et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

How to Cite this Article

Jingwei Song, Jiaying He, Menghua Zhu, et al., “Simulated Annealing Based Hybrid Forecast for Improving Daily Municipal Solid Waste Generation Prediction,” The Scientific World Journal, vol. 2014, Article ID 834357, 7 pages, 2014. https://doi.org/10.1155/2014/834357.