Optimization design and research of simulation system for urban green ecological rainwater by genetic algorithm

This exploration aims to propose an urban green rainwater management model based on urban green ecological rainwater system (GERS) to solve the problem of urban waterlogging caused by urbanization and realize the local recycling of urban rainwater resources. First, the urban one-dimensional rainwater pipe network model and two-dimensional surface model are implemented based on MIKE URBAN model. Next, a green ecological rainwater facility model is implemented through node generalization to evaluate the rainwater pipe network pressure and land water area. Finally, the improved multi-objective optimization non-dominated sorting genetic algorithms-II (NSGA-II) is used to optimize the design and research of urban green ecological rainwater simulation systems. The results show that compared with traditional genetic algorithms and non-dominated sorting genetic algorithms (NSGA), the accuracy of NSGA-II is 96.17% and 88.57%, which greatly improves the application performance of the algorithm. The effectiveness of the algorithm is verified by comparing the performance of traditional genetic algorithm (GA) and improved sorting GA. The research conclusion is that NSGA-II is superior to the conventional design scheme in economy and hydraulic performance. The above results can provide a reference for using green ecological rainwater model to solve urban rainstorms and flood management in complex terrain.