Optimizing channel cross section in irrigation area using improved cat swarm optimization algorithm

This research aimed to design the channel cross section with low water loss in irrigation areas. The traditional methods and models are based on explicit equations which neglect seepage and evaporation losses with low accuracy. To rectify this problem, in this research, an improved cat swarm optimization (ICSO) was obtained by adding exponential inertia weight coefficient and mutation to enhance the efficiency of conventional cat swarm optimization (CSO). Finally, the Fifth main channel of Jiangdong Irrigation area in Heilongjiang Province was taken as a study area to test the ability of ICSO. Comparing to the original design, the reduction of water loss was 20% with low flow errors. Furthermore, the ICSO was compared with genetic algorithm (GA), the particle swarm optimization (PSO) and cat swarm algorithm (CSO) to verify the effectiveness in the channel section optimization. The results are satisfactory and the method can be used for reliable design of artificial open channels.