摘要
利用人工神经网络和遗传程序设计建立了洪水预测模型,将其应用于陡河水库洪水预报,根据实测数据对降水、前雨与净雨的关系进行了挖掘。结果表明:这种方法避免了事先建立具体数学表达式的不足,可以自动寻找最优结构,并具有较高的精度。
Flood forecasting model was established based on artificial neural networks and genetic programming, and applied to flood forecasting in Douhe Reservoir. The model did well in mining relationship between rainfall and pre-rain from measured data and net rain. The results show that the new model can find the best model structure automatically and reach higher calculation precision.
出处
《人民黄河》
CAS
北大核心
2012年第8期41-43,共3页
Yellow River
基金
水利部公益性行业科研专项(200801015)
关键词
人工神经网络
遗传程序
数据挖掘
洪水预报
陡河水库
Artificial Neural Networks
genetic programming
data mining
flood forecasting
Douhe Reservoir
