【摘要】 为了提高冰凌灾害的风险预测的可靠性,针对冰凌灾害风险的动态非线性特征,构建能够识别风险波动变化规律的灰色GMP(1,1,N)-Verhulst组合预测模型,同时引入信息熵理论的知识,提出基于Markov链修正的熵权法灰色组合预测方法。以黄河宁蒙段2005～2014年冰凌灾害风险值作为原始数据序列进行模型拟合,并对2015～2017年的冰凌灾害风险进行预测。计算得出在已知实际冰凌风险值的年份内,灰色Markov-GMP-Verhulst模型的预测精度比单一灰色预测模型更加精确,结合实际情况评估2015～2016、2016～2017年的冰凌灾害风险值,并与Markov链修正的组合模型的预测值进行对比分析,预测结果与实际值的吻合性良好,进一步验证了模型的合理可操作性,以期为黄河宁蒙河段的凌汛灾害防治提供借鉴。更多还原

【Abstract】 In order to improve the reliability of icicle hazard risk prediction aiming at the dynamic nonlinear characteristics of ice-jam disaster risk, a grey GMP(1,1,N)-Verhulst combination forecasting model which can identify the change law of risk fluctuation is constructed. At the same time, the knowledge of information entropy theory is introduced, and the gray combination forecasting method based on Markov chain modification is proposed. The model was fitted with the icicle hazard risk value of the Yellow River Ningxia-Inner Mongolia reaches from 2005 to 2014 as the original data series, and the ice-jam disaster risk from 2015 to 2017 was predicted. The prediction accuracy of the gray Markov-GMP-Verhulst model is more accurate than the single gray prediction model in the year when the actual ice risk value is known. The ice-jam disaster risk values of 2015 to 2016 and 2016 to 2017 are evaluated according to the actual situation. Compared with the predicted values of the Markov chain modified combination model, the prediction results are in good agreement with the actual values, and the reasonable operability of the model is further verified, in order to provide reference for the prevention and control of the flood disaster in the Ningxia-Inner Mongolia Reaches of the Yellow River.更多还原