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| DOI：10.13522/j.cnki.ggps.2020161 |
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| Using GA-RBF Neural Network Model to Calculate the Diversion Capability of the Weishan Sluice |
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LI Shoutao, WANG Juntao, YU Ming, YAO Jingwei, ZHAO Guoping, FAN Yumiao
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1. Yellow River Institute of Hydraulic Research, Zhengzhou 450045, China; 2. Hohai University College of Water Conservancy and Hydropower Engineering, Nanjing 210098, China; 3. Weishan Irrigation District Management Office of Liaocheng City, Liaocheng 252053, China; 4. Yellow River Affairs Bureau of Liaocheng City, Liaocheng 252000, China
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| Abstract: |
| 【Background and Objective】Sluice is an important component in hydraulic projects to control water flow, and its performance and diverting capacity are affected by its operating parameters and ambient environment. Understanding how its diversion capacity varies with these factors is important but not trivial. The objective of this paper is to present a new model to estimate the change in diversion capacity of sluice in response to its operating parameters and environmental factors. 【Method】We took the Weishan sluice in Shandon province as an example. The change in its flowing capacity with factors including the number of its openings, water depth at the back and front of the sluice was analyzed using the radial basis function neural network. Optimization of the network, including the number of its hidden layers, was solved using the genetic algorithm. The model was trained first using measured data, and it was then used to evaluate the performance of the sluice under different operating and environmental conditions.【Result】The trained model was accurate, and compared with the measured data, its average error was 1.64%. Results calculated from the model showed that in flooding seasons, the diversion capacity of the sluice meets the design requirement, while during dry seasons its diversion capacity increased with the reduction in the water depth at the back of the sluice. Considering the dredge to be carried out in the downstream sediment conveyance, the calculated flowing capacity meets the design requirements.【Conclusion】The GA-RBF model was adaptable and accurate for calculating the diversion capacity of the Weishan sluice. |
| Key words: Weishan Sluice; GA-RBF; diversion capacity; prediction |
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