Abstract

The South-to-North Water Diversion Middle Route Project has long water transmission line, complicated operation conditions for water conservancy dispatch, and high water diversion demands. It is important to calculate and analyse the correlation among hydraulic factors for water diversion. At present, the traditional hydraulic empirical formulas are used to evaluate relation of hydraulic elements in Middle Route Project, the parameters need to be manually corrected by measured data during operation, and the flexibility is poor. Model based on genetic programming is suggested for data mining of water conveyance dispatch. Correlativity function can be established automatically by genetic operations including selection, crossover and mutation. The model is applied into the discharge calculation and analysis of water surface curve for typical gate station and canal pool in Middle Route Project. In discharge calculation, the relation function between head difference, gate opening and flow coefficient can be found automatically with genetic programming. Similarly, the relation between downstream water depth, flow and upstream water depth can be achieved by the suggested model. It is shown that the proposed model based on genetic programing would be effective in nonlinear regression for hydraulic factors.

Details

Title
Models of Hydraulic Factors Analysis Based on Genetic Programming for South-to-North Water Diversion Middle Route Project
Author
Chen, Xiaonan 1 ; Chen, Haitao 2 ; Jin, Yanguo 1 ; Feng, Xiaobo 3 ; Ma, Yanjun 1 ; Guo, Fang 1 

 Construction and Administration Bureau of South-to-North Water Diversion Middle Route Project, Beijing, 100038, China 
 School of Water Conservancy, North China University of Water Resources and Electric Power, Zhengzhou, Henan Province, 450045, China 
 Supervision Centre of South-to-North Water Diversion Project, Beijing, 100038, China 
Publication year
2019
Publication date
Sep 2019
Publisher
IOP Publishing
ISSN
17551307
e-ISSN
17551315
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2557866518
Copyright
© 2019. This work is published under http://creativecommons.org/licenses/by/3.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.