2023 Vol.6 Aug.N04

• Title: Reservoir water level prediction based on BP neural network
• Name: Da Liu,Weiping Luo
• Company: Wuhan Textile University School of Mechanical Engineering and Automation, Wuhan, 430200 China
• Abstract:

   In this paper, a high-precision reservoir water level prediction model based on BP neural network is constructed for the monitoring of reservoir water level, which can effectively monitor the reservoir water level and assist the staff to make emergency treatment in time in case of emergency. The model uses the time-by-time water level time series from July 1, 2021 to September 1, 2022 at a water level station in Wuhan, Hubei Province as the data set. The mean absolute error between the predicted water level value and the real water level value of the model is 0.10158, the root mean square error is 0.02628, and the mean absolute percentage error is 0.43033%, with high prediction accuracy and good application prospects.

  
  

• Keyword: BP neural networks; time series; water level prediction;
• DOI: 10.12250/jpciams2023090603
• Citation form: Da Liu.Reservoir water level prediction based on BP neural network [J]. Computer Informatization and Mechanical System,2023,Vol.6,pp.13-15

[1] ZHOU Xingyan, ZENG Hongling, WANG Zunya et al. Climatic Characteristics and Major Meteorological Events over China in 2018[J]. Meteorological Monthly, 2019, 45(04): 543-552.

[2] LI Ying, ZENG Hongling, WANG Guofu et al. Climatic Characteristics and Major Meteorological Events over China in 2019[J]. Meteorological Monthly, 2020, 46(04): 547-555.

[3] DAI Tanlong, WANG Qiuling, WANG Guofu et al. Climatic Characteristics and Major Meteorological Events over China in 2020[J]. Meteorological Monthly, 2021, 47(04): 478-487.

[4] HAN Zhuohui, YAN Changqing. Basin Flood Prediction and Simulation Based on PG-BP Neural Network[J]. Software Guide, 2021, 20(05): 50-55.

[5] Haopeng Li. Research of the Underground Water Level Prediction Model in Deep Foundation Pit Engineering[J]. Applied Mechanics and Materials, 2014, 675-677: 881-884.

[6] LIU Guangxing, LI Qiaohua. The research of BP neural network based on particle swarm optimization in groundwater level prediction[J]. Electronic Test ,2019(07): 51-52.

[7] Quan Yalei, Yang Xuhong. A Method For Alarming Water Level of Boiler Drum on Nuclear Power Plant Based on BP Neural Network[J]. 2014 10TH INTERNATIONAL CONFERENCE ON NATURAL COMPUTATION (ICNC), 2014: 83-87.

[8] Shuyan Guo, Chunlai Dong. Forecasting Method of Hulun Lake Water Level Based on Wavelet Analysis and BP Neural Network[J]., 2011: 426-429.

ZHONG Ying, WANG Bingwen. BP Network Sequence Prediction Model Based on Genetic Algorithm[J]. Systems Engineering and Electronics, 2002(04): 9-11