| 王汉涛， 张潇潇.仿生算法优化BP神经网络在降雨空间插值中的应用Journal of Water Resources and Water Engineering[J].,2019,30(3):106-112 |
| 仿生算法优化BP神经网络在降雨空间插值中的应用 |
| Application of bionic algorithms optimizing BP neural network in spatial interpolation of rainfall |
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| DOI：10.11705/j.issn.1672-643X.2019.03.16 |
| 中文关键词: 遗传算法 粒子群算法 蚁群算法 BP神经网络 降雨空间插值 三峡区间流域 |
| 英文关键词: genetic algorithm particle swarm optimization algorithm ant colony algorithm BP neural network rainfall spatial interpolation Three Gorges region basin |
| 基金项目:国家“十二五”水专项(2014ZX07104-005) ; 国家重点研发计划项目(2016YFC0402210) |
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| 中文摘要: |
| 人工神经网络能够充分挖掘已知样本中的规律，从而对未观测数据进行预测，可应用于降雨量空间插值计算中。在BP神经网络进行降雨空间插值的基础上，引入遗传、粒子群和蚁群3种仿生算法对BP神经网络初始权值和阈值进行优化，将优化后的BP神经网络应用于三峡区间流域年、月和日3个时间尺度的降雨空间插值中。结果表明：仿生算法对BP神经网络初始权值和阈值优化求解后，降低了BP神经网络陷入局部最小以及过拟合的风险，在插值过程中表现出较好的稳定性，取得了理想的插值结果。 |
| 英文摘要: |
| The artificial neural network can dig out the regulation of the observed data fully to have a prediction to the unobserved data, and can be applied in the spatial interpolation of rainfall. Based on the traditional BP neural network in spatial interpolation of rainfall, this paper introduces the genetic algorithm, particle swarm optimization and ant colony algorithm to optimize the initial weights and thresholds of BP neural network, and are applied in the spatial interpolation of rainfall of year, month and day such three temporal scales in the Three Gorges region. The results showed that after the optimization of initial weights and thresholds of BP neural network by bionic algorithms, it can reduce risk of BP trapping in the partial smallest and the over fitting. There is a better stability in the interpolation process to get the ideal interpolation. |
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