%0 Journal Article
%A LIU Ying
%A ZHENG Rong-wei
%A QI Yan-fang
%A CHEN Hong-cai
%T Optimizing Design of Pipe Network in Micro-irrigation System Using SVMs-GA
%D 2022
%R 10.11988/ckyyb.20210137
%J Journal of Yangtze River Scientific Research Institute
%P 71-75
%V 39
%N 5
%X The aim of this research is to optimize the combination mode of pipe network in agricultural pipeline irrigation, improve irrigation efficiency and cut irrigation costs. Support vector machine (SVM) coupled with genetic algorithm (GA) was employed to optimize the model, and the optimal combination of the number of standard sections of branch pipes with different diameters that met the constraints and the objective function was obtained. The objective function was to minimize the cost per unit area of pipeline under the assumption of unlimited irrigation area; the decision variables were the number of standard sections of branch and capillary; the constraint conditions were the maximum allowable pressure difference of the system and the minimum number of pipes constituting the pipe network. Results showed that when capillary pipes were laid in both directions, the cost of pipes per unit area was the lowest, 8 755.7 yuan/hm<sup>2</sup>, the irrigation area was 24.15 hm<sup>2</sup>, and the water head difference of the pipe network reached 97.6%-99.7% allowed by the system. Compared with one-way laying, the cost of pipe per hectare of two-way laying was reduced by about 6.5%, and the irrigation area was increased by about 103%. Compared with the results in existing literature, the cost per hectare of pipeline decreased by 5%, and the irrigation area increased by 23%. In conclusion, support vector machine coupled with genetic algorithm can better optimize the design of pipe network, and provides a reference for agricultural water-saving irrigation.
%U http://ckyyb.crsri.cn/EN/10.11988/ckyyb.20210137