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基于打洞函数法的BP神经网络水文预报方法

The BP Neural Network Hydrological Forecasting Algorithm Based on Tunneling Function Method

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【作者】 王胜刚张莹徐应涛

【Author】 WANG Shenggang ZHANG Ying XU Yingtao School of Agriculture and Biotechnology, Jinhua College of Profession and Technology,Jinhua Zhejiang 321017,China College of Mathematics,Physics and Information Science,Zhejiang Normal University,Jinhua Zhejiang,321004,China

【机构】 金华职业技术学院农业与生物工程学院浙江师范大学数理与信息工程学院

【摘要】 BP神经网络是目前水文预报中应用较为广泛的方法,但存在收敛速度慢、易陷入局部最优的缺陷.由此提出了基于全局优化打洞函数法的水文预报方法,把打洞函数法和BP神经网络相结合,利用打洞函数使BP算法跳出当前局部极小点,得到一个函数值更小的极小点,循环运算直至找到全局极小点.实验表明该水文预报方法能够提高预报精度,显示了良好的适用性.

【Abstract】 BP neural network is widely used in hydrological forecasting.Aiming at the handicaps in present methods such as slow convergence and easily getting into local optimization, this paper presents a novel hydrological forecasting method based on the tunneling function which is one of the effective deterministic methods.The tunneling function method can find a lower minimizer by leaving the minimizer previously found.By repeating these processes,a global minimizer can be obtained at last.Experiments show the proposed method not only can obtain high accuracy in flood forecasting,but also has longer effective real-time.The hydrological forecasting method can be used in operational hydrological forecasting.

【基金】 国家自然科学基金(11001248)
  • 【文献出处】 运筹学学报 ,Operations Research Transactions , 编辑部邮箱 ,2011年04期
  • 【分类号】O224;TP183;P338
  • 【被引频次】9
  • 【下载频次】109
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