基于BP神经网络的黄河中上游河段不平衡水量预测

针对黄河水量统一调度工作中,中上游河段出现的水量不平衡问题,以刘家峡—头道拐河段为例,采用水量平衡公式计算1999~2012年刘家峡—头道拐河段的不平衡水量,并运用BP神经网络技术和方法研究了刘家峡—头道拐河段不平衡水量的变化规律,预测了刘家峡—头道拐河段的不平衡水量。结果表明,BP神经网络模型预测效果较好、精度较高。

Prediction of Water Unbalance in Upper and Middle Reaches of Yellow River Based on BP Neural Network

In review of water imbalance phenomenon of upper and middle reaches of the Yellow River in water regulation, taking Liujiaxia-Toudaoguai river reach as an example, water balance formula was used to calculate imbalance water yield (1999 to 2012). And then the change rule of water balance difference was analyzed and imbalance water yield was predicted by using BP neural network. The results show that the prediction effect of BP neural network model is comparatively well.