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人工神经网络在径流影响因子滞后性研究中的应用
Application of ANN in study of hysteretic nature of factors influencing inflow runoff
【摘要】 根据径流量的影响因素往往具有滞后性的特点,在构建神经网络时,从模型复杂度、训练精度、预测精度等方面综合分析了该特性的影响大小,获得了分析滞后性影响的方法。实例表明该方法能够准确判断出滞后时段的大小,为提高径流预报的准确性提供了一条有效的途径。
【Abstract】 The hysteretic nature of runoff’s influencing factors’is considered,the influencing degree of the hysteretic nature is tested from aspects of complexity,training precision,prediction accuracy of model during structuring ANN model,then the method of analyzing hysteretic nature’s influence is advanced.The result of example study demonstrates that the lag effect time can been accurately predicted by the way,an effective way is given to improve the accuracy of runoff forecast.
【关键词】 人工神经网络;
入库径流;
滞后性;
【Key words】 Artificial Neural Network(ANN); inflow runoff; hysteretic nature;
【Key words】 Artificial Neural Network(ANN); inflow runoff; hysteretic nature;
【基金】 国家自然科学基金No.50279041;国家高技术研究发展计划(863)No.2005AA113150~~
- 【文献出处】 计算机工程与应用 ,Computer Engineering and Applications , 编辑部邮箱 ,2009年30期
- 【分类号】P333.1;TP183
- 【被引频次】5
- 【下载频次】163