陆冬磊, 吴春峰, 段胜刚, 罗宝章, 徐碧瑶, 刘弘. 应用灰色模型GM(1,1)预测上海市副溶血性弧菌引起的食源性疾病发病率[J]. 环境与职业医学, 2015, 32(8): 728-730. DOI: 10.13213/j.cnki.jeom.2015.14607
引用本文: 陆冬磊, 吴春峰, 段胜刚, 罗宝章, 徐碧瑶, 刘弘. 应用灰色模型GM(1,1)预测上海市副溶血性弧菌引起的食源性疾病发病率[J]. 环境与职业医学, 2015, 32(8): 728-730. DOI: 10.13213/j.cnki.jeom.2015.14607
LU Dong-lei , WU Chun-feng , DUAN Sheng-gang , LUO Bao-zhang , XU Bi-yao , LIU Hong . Forecasting of Foodborne Disease Caused by Vibrio parahaemolyticus in Shanghai using Grey Model GM (1, 1)[J]. Journal of Environmental and Occupational Medicine, 2015, 32(8): 728-730. DOI: 10.13213/j.cnki.jeom.2015.14607
Citation: LU Dong-lei , WU Chun-feng , DUAN Sheng-gang , LUO Bao-zhang , XU Bi-yao , LIU Hong . Forecasting of Foodborne Disease Caused by Vibrio parahaemolyticus in Shanghai using Grey Model GM (1, 1)[J]. Journal of Environmental and Occupational Medicine, 2015, 32(8): 728-730. DOI: 10.13213/j.cnki.jeom.2015.14607

应用灰色模型GM(1,1)预测上海市副溶血性弧菌引起的食源性疾病发病率

Forecasting of Foodborne Disease Caused by Vibrio parahaemolyticus in Shanghai using Grey Model GM (1, 1)

  • 摘要: 目的 建立灰色模型GM(1,1),预测上海市副溶血性弧菌引起的食源性疾病的发病率。

    方法 利用2007-2010年上海市食源性疾病监测数据,运用Excel 2010,建立GM(1,1)模型,进行精度及适用性检验,预测2011、2012年发病率并验证。

    结果 GM(1,1)预测模型为X(t+1)=124.32e0.59t-47.14,关联度rt=0.614,后验差比值C=0.24,小误差概率P=1,发展系数-α=0.59,模型预测2011、2012年发病的平均相对误差分别为57.48%、3.90%。

    结论 建立的GM (1,1)模型精度好,谨慎适用短期(2~3年)预测;预测上海市副溶血性弧菌引起的食源性疾病的发病率呈上升趋势。

     

    Abstract: Objective To forecast the incidence of foodborne disease caused by Vibrio parahaemolyticus (VP) in Shanghai by establishing grey model GM (1, 1).

    Methods The Shanghai foodborne disease surveillance data in 2007-2010 were processed by Excel 2010 and used to build GM (1, 1) model. After tests of accuracy and applicability, the model was used to forecast the incidence rate of VP-related foodborne disease in 2011 and 2012 for verification.

    Results The GM (1, 1) prediction model established was X(t+1)=124.32e0.59t-47.14, rt (relativity)=0.614, C (posterior error ratio)=0.24, P (small error probability)=1, -α (development coefficient)=0.59. The average relative error of model forecast results versus actual data for 2011 and 2012 was 57.48% and 3.90% respectively.

    Conclusion The precision of the GM (1, 1) model warrants application with caution in shorttime (2-3 years) forecast. The predicted incidence rate of foodborne disease caused by Vibrio parahaemolyticus in Shanghai is increased according to the established model.

     

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