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Abstract and Applied Analysis
Volume 2014, Article ID 698632, 7 pages
http://dx.doi.org/10.1155/2014/698632
Research Article

The Big Data Processing Algorithm for Water Environment Monitoring of the Three Gorges Reservoir Area

1College of Communication Engineering, Chongqing University, Chongqing 400044, China
2School of Automation, Chongqing University, Chongqing 400044, China

Received 20 April 2014; Revised 27 June 2014; Accepted 27 June 2014; Published 5 August 2014

Academic Editor: Shen Yin

Copyright © 2014 Yuanchang Zhong 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.

Abstract

Owing to the increase and the complexity of data caused by the uncertain environment, the water environment monitoring system in Three Gorges Reservoir Area faces much pressure in data handling. In order to identify the water quality quickly and effectively, this paper presents a new big data processing algorithm for water quality analysis. The algorithm has adopted a fast fuzzy C-means clustering algorithm to analyze water environment monitoring data. The fast clustering algorithm is based on fuzzy C-means clustering algorithm and hard C-means clustering algorithm. And the result of hard clustering is utilized to guide the initial value of fuzzy clustering. The new clustering algorithm can speed up the rate of convergence. With the analysis of fast clustering, we can identify the quality of water samples. Both the theoretical and simulated results show that the algorithm can quickly and efficiently analyze the water quality in the Three Gorges Reservoir Area, which significantly improves the efficiency of big data processing. What is more, our proposed processing algorithm provides a reliable scientific basis for water pollution control in the Three Gorges Reservoir Area.