scholarly journals Research on Water Quality Assessment Model Based on Improved Three-Dimensional Nemerow Index Method and Firefly Algorithm

2017 ◽  
Vol 7 (2) ◽  
pp. 47
Author(s):  
Jian Cao ◽  
Zheng-Long Li ◽  
Yuan-Biao Zhang
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Firefly Algorithm ◽  
Human Life ◽  
Three Dimensional ◽  
Water Quality Assessment ◽  
Assessment Model ◽  
Index Method ◽  
Threshold Setting ◽  
Ongoing Concern

Monitoring water quality is a subject of ongoing concern and study since water quality is closely related to human life. Although Nemerow index method is widely used in water quality assessment, the artificial threshold setting may lead to some errors. In this study, we improved the traditional Nemerow index method and built a three-dimensional water quality assessment model combined with the modified firefly algorithm (FA). Then, we applied the improved three-dimensional Nemerow index method to evaluate 100 random water samples. Compared with the traditional method, the improved one proved to be more objective, scientific and practical.

Water quality assessment by pollution-index method in the coastal waters of Hebei Province in western Bohai Sea, China

2011 ◽  
Vol 62 (10) ◽  
pp. 2220-2229 ◽  
Author(s):  
Shuguang Liu ◽  
Sha Lou ◽  
Cuiping Kuang ◽  
Wenrui Huang ◽  
Wujun Chen ◽  
...  
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Coastal Waters ◽  
Bohai Sea ◽  
Pollution Index ◽  
Water Quality Assessment ◽  
Hebei Province ◽  
Index Method

scholarly journals A Multiagent Dynamic Assessment Approach for Water Quality Based on Improved Q-Learning Algorithm

2013 ◽  
Vol 2013 ◽  
pp. 1-7 ◽  
Author(s):  
Jianjun Ni ◽  
Li Ren ◽  
Minghua Liu ◽  
Daqi Zhu
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Water Resource Management ◽  
Learning Algorithm ◽  
Dynamic Assessment ◽  
Water Quality Assessment ◽  
Assessment Model ◽  
Fuzzy Membership Function ◽  
Q Learning ◽  
Interaction Factor

The dynamic water quality assessment is a challenging and critical issue in water resource management systems. To deal with this complex problem, a dynamic water assessment model based on multiagent technology is proposed, and an improved Q-learning algorithm is used in this paper. In the proposed Q-learning algorithm, a fuzzy membership function and a punishment mechanism are introduced to improve the learning speed of Q-learning algorithm. The dynamic water quality assessment for different regions and the prewarning of water pollution are achieved by using an interaction factor in the proposed approach. The proposed approach can deal with various situations, such as static and dynamic water quality assessment. The experimental results show that the water quality assessment based on the proposed approach is more accurate and efficient than the general methods.

Establishment and Application of Water Quality Assessment Model for Jiaozhou Bay Basin

2012 ◽  
Vol 518-523 ◽  
pp. 1165-1170 ◽  
Author(s):  
Chao Liu ◽  
Hui He ◽  
Xiao Hui Tan ◽  
Ai Li Gao ◽  
Song Xue
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Bp Neural Network ◽  
Jiaozhou Bay ◽  
Water Quality Assessment ◽  
Training Sample ◽  
Assessment Method ◽  
Assessment Model ◽  
Water Quality Status ◽  
Effectiveness Of Training

In this paper, a comprehensive water quality assessment model for the seagoing rivers of the Jiaozhou Bay basin was established based on a BP neural network. In the situation investigation, a list of main assessment indexes was selected, comprising COD, permanganate, DO, ammonia, volatile hydroxybenzene and mineral oil. Then Environmental Quality Standards for Surface Water was used as the training sample and comprehensive assessment was conducted for the rivers. In Comparison with results from the conventional single-factor assessment method, this model not only responded to the comprehensive river water quality status, but also improved the speed and effectiveness of training, saving time and increasing accuracy of the assessment model through a series of design optimizations.

Research on the New Assessment Model of Water Source Quality Based on Maximum Entropy Principle

2011 ◽  
Vol 403-408 ◽  
pp. 2123-2126
Author(s):  
Ren Qiang Lu
Keyword(s):  
Water Quality ◽  
Quality Assessment ◽  
Maximum Entropy ◽  
Structural Changes ◽  
Maximum Entropy Principle ◽  
Water Source ◽  
Water Quality Assessment ◽  
Assessment Model ◽  
Lake System ◽  
Entropy Principle

Water source quality is the crucial factor to determine the safety and reliability of urban water supply, and the effective water quality assessment is the premise for water source conservation. Taking a lake system as an example, firstly, the maximum entropy principle was used to analyze the evolution mechanism of the structural changes of lake system. And the nonlinear coupling between the different subsystems of lake system was also analyzed. Secondly, the Self-Organizing feature map neural network was used to simulate the dynamic evolution process of lake system. Finally, a new assessment model for water source quality was established based on the maximum entropy principle. Through application it found that this model achieved the quantitative evaluation of water source quality effectively, and surmounted the inadequate that the precious water quality assessment methods had to determination the weights of the different water quality indicators subjectively.

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