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Water Quality Monitoring Based on Fish Movement Characteristics and XGBoost |
CHENG Shu-hong1,ZHANG Shi-jun1,LI Lei-hua1,ZHANG Dian-fan2 |
1. Institute of Electrical Engineering, Yanshan University, Qinhuangdao, Hebei 066004, China
2. Yanshan University Science Park, Qinhuangdao, Hebei 066004, China |
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Abstract Realization of water quality monitoring by combining fish movement behavior with XGBoost classifier.According to the influence of water quality on the movement of fish, some characteristic parameters were introduced, such as center distance index, dispersion and distribution area, which were extracted from the movement behavior of fish. Secondly, five characteristic parameters of swimming distance, velocity, acceleration, curvature and neighborhood of fish in normal and abnormal water quality were extracted, and water quality anomaly evaluation factor database was established. Finally, different evaluation factors were input to XGBoost classifier for classification and recognition. The experimental results showed that the three characteristic parameters of the center distance index, dispersion and distribution area can reflect the water quality condition high efficiency and accurately.
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Received: 01 September 2017
Published: 06 July 2018
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Corresponding Authors:
CHENG Shuhong
E-mail: shhcheng@ysu.edu.cn
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