BAIYun,YANZheng-jie,ZHANGJin,et al.Prediction of Daily Water Supply Based on Multi-granularity Leakage Integral Echo State Network[J].China Water & Wastewater,2023,39(9):50-56.
Prediction of Daily Water Supply Based on Multi-granularity Leakage Integral Echo State Network
China Water & Wastewater[ISSN:1000-4062/CN:12-1073/TU]
volume:
第39卷
Number:
第9期
Page:
50-56
Column:
Date of publication:
2023-05-01
- Keywords:
- X11 decomposition algorithm; granularity mining; echo state network; water supply prediction
- Abstract:
- Aiming at the uncertain impact of multi-granularity factor coupling on urban daily water supply, a combined prediction model X11+LiESN based on multi-granularity mining and leakage integral echo state network (LiESN) was proposed to improve the prediction accuracy of urban daily water supply. The effectiveness of the model was verified by using daily water supply data of a water treatment plant in Chongqing from January 1, 2018 to December 31, 2020. The mean absolute percentage error (MAPE) of the proposed model was 3.42%, and the coefficient of determination (R2) was 0.862. Compared with single models of LiESN, extreme learning machine (ELM) and BP neural network（BPNN）, the model exhibited higher prediction accuracy and better description of daily water supply trend, and thus showed its effectiveness and application potential.
Last Update:
2023-05-01