基于人工神经网络的黄河下游防断流研究  

Study on Preventing No-flow from Appearing in the Lower Yellow River Based on Artificial Neural Network

作　　者：赵全升[1] 牟晓燕[1] 戴其祥[2] 邹剑峰[2] 詹志习[2] 吴国宏[2] 

机构地区：[1]青岛大学,山东青岛266071 [2]黄河水利委员会勘测规划设计研究院,河南郑州450003

出　　处：《工程勘察》2003年第1期20-23,共4页Geotechnical Investigation & Surveying

摘　　要：应用人工神经网络建立下游枯季迳流预测的BP神经网络模型。在此基础上 ,针对上游不同的来水水平 ,在确保下游不出现断流情况下 ,应用BP神经网络模型反算下游引黄量 ,据此提出花园口水文站来水量和下游引水量组合方案 ,可为黄河流域水资源的统一调度、管理 。Models of BP Artificial Neural Network for the forecast of dry season runoff in the Lower Yellow River are set up by using artificial neural network.According to different coming water conditions of the runoff discharge at Huayuankou station the supporting water quantity of the Lower Yellow River is calculated on the base of preventing no\|flow from appearing.The combination scheme for the relationship between the discharge at Huayuankou station and the supporting water quantity of the Lower Yellow River may provide the scientific basis for the integrated dispatch and management of water resources in the Yellow River basin,especially for preventing the no flow from appearing again.

关 键 词：人工神经网络 黄河下游 断流 引水量 水资源 

分 类 号：TV882.1[水利工程—水利水电工程]