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首页> 外文期刊>Mathematical Problems in Engineering >Design of Deep Belief Networks for Short-Term Prediction of Drought Index Using Data in the Huaihe River Basin
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Design of Deep Belief Networks for Short-Term Prediction of Drought Index Using Data in the Huaihe River Basin

机译：淮河流域干旱指数短期预报的深信度网络设计

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摘要

With the global climate change, drought disasters occur frequently. Drought prediction is an important content for drought disaster management, planning and management of water resource systems of a river basin. In this study, a short-term drought prediction model based on deep belief networks (DBNs) is proposed to predict the time series of different time-scale standardized precipitation index (SPI). The DBN model is applied to predict the drought time series in the Huaihe River Basin, China. Compared with BP neural network, the DBN-based drought prediction model has shown better predictive skills than the BP neural network for the different time-scale SPI. This research can improve drought prediction technology and be helpful for water resources managers and decision makers in managing drought disasters.
机译：随着全球气候变化，干旱灾害频繁发生。干旱预测是干旱灾害管理，流域水资源系统规划与管理的重要内容。在这项研究中，提出了一种基于深度信念网络（DBN）的短期干旱预测模型，以预测不同时标标准化降水指数（SPI）的时间序列。 DBN模型被用于预测淮河流域的干旱时间序列。与BP神经网络相比，基于DBN的干旱预测模型在不同的时标SPI上具有比BP神经网络更好的预测能力。这项研究可以改善干旱预测技术，并有助于水资源管理者和决策者管理干旱灾害。

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  • 来源
    《Mathematical Problems in Engineering》 |2012年第5期|p.24.1-24.16|共16页
  • 作者

    Junfei Chen; Qiongji Jin; Jing Chao;

  • 作者单位

    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China,Business School, Hohai University, Nanjing 210098, China;

    State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 210098, China,Business School, Hohai University, Nanjing 210098, China;

    State Key Laboratory for Novel Software Technology, Nanjing University, Nanjing 210093, China;

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