Monitoring of Flooding Water under Coal Mine Based on Improved Fuzzy Clustering

Abstract:

Due to the complicated coal mine flooding water quality monitoring data, in order to extract the effective data from vast amounts of data, this article used the fuzzy clustering to analyze the monitoring data processing. This study makes a brief analysis of monitoring data structure, then analyzes the shortcomings of fuzzy C mean clustering algorithm (FCM),which also proposes fuzzy C-means algorithm based on particle swarm optimization (PSO-FCM). Finally samples of the underground water data are used to carry out the instance simulation. The experiment results showed that in dealing with data samples. The algorithm had some advantages and it was worthy of research.

• Periodical: Applied Mechanics and Materials (Volumes 580-583)
• Pages: 2713-2716
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.580-583.2713
• Online since: July 2014
• Authors: Meng Ya Nie, Meng Ran Zhou, Xue Qiang Fu
• Keywords: FCM, Fuzzy Clustering, PSO-FCM, Water Quality Monitoring

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