摘要
为了提高年径流量预测的精度,将灰色系统理论的弱化缓冲算子和人工神经网络相结合,提出一种新的年径流预测方法——引入灰色弱化缓冲算子的人工神经网络组合预测方法,并以兰州站年径流过程计算为例,验证了该方法的合理性。结果表明,预测结果精度较高,可见将引入灰色弱化缓冲算子的人工神经网络组合预测方法用于年径流预测具有可行性。
In order to improve the accuracy of prediction of annual runoff, a new forecast algorithm of annual runoff is proposed by combining the weakening buffer operator of grey systems theory and artificial neural network. Taking annual runoff calculation of Lanzhou hydrologic station for an example, the rationality of the proposed method is verified. The results indicate that the proposed method is feasible with higher precision for annual runoff forecasting.
出处
《水电能源科学》
北大核心
2013年第7期13-15,114,共4页
Water Resources and Power
基金
国家自然科学基金资助项目(41061053)
云南省自然科学基金资助项目(2009ZC005X)
关键词
年径流量
人工神经网络
灰色系统
弱化缓冲算子
预测
annual runoff
artificial neural network
grey systems
weakening buffer operator
forecast
