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Water Pollution Prevention and Control Project, 2021, 2(3); doi: 10.38007/WPPCP.2021.020302.

Evaluation on Intelligent Assessment Software of Water Pollution Based on Bayesian Network

Author(s)

Yunbo Li

Corresponding Author:
Yunbo Li
Affiliation(s)

Department of Information Engineering, Heilongjiang International University, Harbin 150025, China

Abstract

With the acceleration of industrialization and urbanization, the irrational exploitation of groundwater resources is increasingly intensified, the pollution problem is becoming increasingly serious, and the water pollution situation is not optimistic. By evaluating the quality of groundwater, people can reflect and grasp the quality and evolution trend of groundwater, thus providing a basis for the protection and development of groundwater, and a correct and efficient evaluation method is a necessary condition to achieve this goal. Due to a large number of monitoring of groundwater quality, there are a lot of unstable factors, making the assessment of groundwater quality become a very difficult problem. At present, the commonly used evaluation methods include single index method and artificial neural network method. The above methods of water quality assessment are applicable to various situations, but when used under the same conditions, the assessment results vary greatly. Fuzzy comprehensive evaluation is currently recognized as the most reliable evaluation method, but its calculation process is relatively complicated, and it is difficult to evaluate it in the case of a large number of samples and indicators. Through the analysis of experimental data, it was found that the probability of water quality reaching the standard was 34%, and the Bayesian network algorithm was of great significance to the prediction and diagnosis of water pollution. Bayesian network algorithm had better effect than traditional algorithm, and was 17.4% higher overall.

Keywords

Ant Colony, Intelligent Assessment and Analysis of Water Pollution, Prediction and Analysis of Various Water Quality Indicators, Diagnostic Analysis of Various Water Quality Indicators

Cite This Paper

Yunbo Li. Evaluation on Intelligent Assessment Software of Water Pollution Based on Bayesian Network. Water Pollution Prevention and Control Project (2021), Vol. 2, Issue 3: 12-21. https://doi.org/10.38007/WPPCP.2021.020302.

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