Chapter 5 introduces the forecasting effect of the long term runoff forecasting model.
第四章具体介绍了预测模型的数据库设计与实现。
This paper presents a forecasting model of runoff to Wuyandong subterranean stream system by BP ANN based on the data of precipitation and flux in Luota, west Hunan.
采用湖南洛塔地区屋檐洞地下河系统降水—径流资料训练BP人工神经网络，建立了该系统的径流预测模型。
Coupling partial least-squares regression and neural network in the article, the forecasting model of the quantity of runoff is established.
将偏最小二乘回归与神经网络耦合，建立了径流量预报模型。
The time span of middle-term optimization model equal foreseeable period of runoff forecasting (3 to 7 days), and the optimization period is one day.
中期模型优化的时间跨度等于中期入库径流预报的预见期（3-7天），优化时段为一天。
Based on the recognition of hydrological drought and the runoff forecasting during the drought period, a forecasting model of hydrological drought is established.
通过水文干旱识别和枯水期径流量预估，建立了供水系统水文干旱的预测模型。
The combined use of above method and the metabolic fractal interpolation forecasting model provides new idea and new method for improving the runoff prediction precision.
并将该方法与新陈代谢分形插值预测模型结合使用，为有效提高径流预测精度提供了新思路和新方法。
The combined use of above method and the metabolic fractal interpolation forecasting model provides new idea and new method for improving the runoff prediction precision.
并将该方法与新陈代谢分形插值预测模型结合使用，为有效提高径流预测精度提供了新思路和新方法。
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