河道在城市的排水系统中尤为重要,本文从宏观方面运用BP人工神经网络构建河道水位预测模型,通过模型预测的值,在三维系统中展示,实现城市内涝内河的灾害点空间分布.该模型的优势:取用数据较少,精度高,能够很好地模拟暴雨条件下昆明市盘龙江油管桥水位.本文的研究成果有助于城市内涝研究.%The river is particularly important in the city's drainage system. In this paper, BP neural network is used to construct the river water level forecasting model from the macroscopic aspect. Through the model predicted value, it is displayed in the three-dimensional system to achieve the spatial distribution of disaster points in the city's waterlogged river. The advantages of the model: access to less data, high precision, can be a good simulation of rainstorm conditions in Kunming Panlongjiang Youguanqiao water level. The research results of this paper are helpful to the study of urban waterlogging.
展开▼
