Feature Extraction of Marine Water Pollution Based on Data Mining
| Autor: | Xiangwei Bai, Jianhong Cui, Haixia Lin |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2021 |
| Předmět: |
Physics and Astronomy (miscellaneous)
General Mathematics 0208 environmental biotechnology Feature extraction Sewage K-means clustering 02 engineering and technology 010501 environmental sciences 01 natural sciences Cosine Distance Method Computer Science (miscellaneous) Cluster analysis Water pollution 0105 earth and related environmental sciences Plastic bag business.industry Water pollutants lcsh:Mathematics Environmental engineering data mining lcsh:QA1-939 020801 environmental engineering polygon area method abnormal water quality Chemistry (miscellaneous) Environmental science Water quality business discrimination |
| Zdroj: | Symmetry, Vol 13, Iss 355, p 355 (2021) Symmetry Volume 13 Issue 2 |
| ISSN: | 2073-8994 |
| Popis: | The ocean occupies more than two-thirds of the earth’s area, providing a lot of oxygen and materials for human survival and development. However, with human activities, a large number of sewage, plastic bags, and other wastes are discharged into the ocean, and the problem of marine water pollution has become a hot topic in the world. In order to extract the characteristics of marine water pollution, this study proposed K-means clustering technology based on cosine distance and discrimination to study the polluted water. In this study, the polygonal area method combined with six parameters of water quality is used to analyze the marine water body anomalies, so as to realize the rapid and real-time monitoring of marine water body anomalies. At the same time, the cosine distance method and discrimination are used to classify marine water pollutants, so as to improve the classification accuracy. The results show that the detection rate of water quality anomalies is more than 88.2%, and the overall classification accuracy of water pollution is 96.3%, which proves the effectiveness of the method. It is hoped that this study can provide timely and effective data support for the detection of marine water bodies. |
| Databáze: | OpenAIRE |
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