Research on Section Optimization of Water Quality Monitoring Based on Comprehensive Hierarchical Clustering

Authors

Xiaofeng Lian, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China;
Peng Sen, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China;
Xiaoyi Wang, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China;
Zaiwen Liu, School of Computer and Information Engineering, Beijing Technology and Business University, Beijing, 100048, China;

Abstract

Abstract: In order to optimize the layout of water quality monitoring section of river, lake and reservoir effectively, a new method for water quality monitoring section optimization was proposed based on comprehensive hierarchical clustering (CHC). A normalized matrix was constructed according to the original monitoring data of water quality. The method calculated the similarity to obtain the affinity-disaffinity relationship among the monitoring variables by 5 different distance algorithms, and then clustered the data set automatically by 4 different connection algorithms. Moreover, taking the correlation coefficient as the evaluation criteria, optimal hierarchical clustering algorithm was selected. With the generation of corresponding optimal clustering tree matrix, the section monitoring sites were set optimally to obtain the monitoring data reflecting the water quality of whole area, thus the monitoring water quality could be more effectively. The experimental results show that this method is practical and integrated highly, thus has good prospect.

Recommended Citation

Lian, Xiaofeng; Sen, Peng; Wang, Xiaoyi; and Liu, Zaiwen (2020) "Research on Section Optimization of Water Quality Monitoring Based on Comprehensive Hierarchical Clustering," Journal of System Simulation: Vol. 27: Iss. 7, Article 22.
Available at: https://dc-china-simulation.researchcommons.org/journal/vol27/iss7/22

First Page

1563

Revised Date

2014-10-30

DOI Link

https://doi.org/

Last Page

1569

CLC

TP391.9

Recommended Citation

Lian Xiaofeng, Peng Sen, Wang Xiaoyi, Liu Zaiwen. Research on Section Optimization of Water Quality Monitoring Based on Comprehensive Hierarchical Clustering[J]. Journal of System Simulation, 2015, 27(7): 1563-1569.