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基于灰色残差马尔可夫模型的郑州市旱涝灾害预测 被引量:5

Drought and Flood Disaster Prediction of Zhengzhou City Based on Grey-Markov Model
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摘要 针对旱涝灾害影响范围广、发生频率高和难以准确预测的情况,利用马尔可夫状态转移矩阵与DGM(1,1)预测模型的互补优势,构建了灰色残差马尔可夫预测模型.选取郑州市某60 a的年降水量作为历史数据,运用均值-标准差旱涝等级划分法得到干旱和雨涝的降水量临界值,从而取定上、下灾变点,分别建立干旱和雨涝日期灾变序列,并对序列进行建模求解.结果表明,灰色残差马尔可夫预测模型计算简便、精度较高.预测结果可以为郑州地区的旱涝预测及防灾减灾工作提供借鉴. The drought and flood disaster has features with wide influence,high frequency and hard to forecast. Based on the basic principle of grey model and the complementary advantage of Markov state transition matrix,the grey Markov prediction residuals optimization model was established. We chose the annual precipitation during 60 years in Zhengzhou as historical data and fixed the abnormal sequence,then established the prediction model of drought and flood. Using mean-standard deviation drought and flood classification method,the precipitation thresholds of drought and waterlogging were obtained. Thereby taking fixed upper and lower catastrophe point,the date disaster sequences of drought and waterlogging were built. At last,the sequence was modeled and solved. The result shows that the optimized prediction models of grey Markov are simpler and more accurate than the basic grey model and can be used as a reference for the disaster prevention and mitigation of Zhengzhou City.
出处 《华北水利水电大学学报(自然科学版)》 2015年第5期1-4,9,共5页 Journal of North China University of Water Resources and Electric Power:Natural Science Edition
基金 国家自然科学基金资助项目(71271086) 河南省科技厅重点攻关项目 河南省协同创新平台建设与管理模式研究(1421031023) 2015年河南省高等学校重点科研项目资助计划 高等学校科技管理创新模式研究(15A630005)
关键词 DGM(1 1)模型 降水量 马尔可夫链 残差灾变序列 DGM(1 1) model precipitation Markov chain residual abnormal sequence
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