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- W2783134557 abstract "The traditional optimal operation method of pumping station had many shortcomings, such as strong dependence on the experience of engineers, high design and maintenance costs, and complicated operation. Based on the principle of machine learning, a set of optimal operation method of pumping station was established. According to this method, the pump characteristic curve data from SCADA were selected, and k-medoids algorithm was used to filter data noise. Then the BP neural network was used to train pump characteristic curve. Finally, the genetic algorithm was used to solve the minimum power consumption of unit water in pumping station. Experiments have proved that the method could automatically and effectively filter noise, and establish a higher precision model, and get the optimal solution. This method have realized the automatic operation of pumping station under weak manual intervention, and it had good versatility. After further research, it could be popularized and applied in engineering." @default.
- W2783134557 created "2018-01-26" @default.
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- W2783134557 date "2017-11-01" @default.
- W2783134557 modified "2023-09-23" @default.
- W2783134557 title "Research on optimal operation method of pumping station based on machine learning" @default.
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- W2783134557 doi "https://doi.org/10.1109/ei2.2017.8245334" @default.
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