【摘要】：機(jī)場安檢的危險(xiǎn)品數(shù)量具有動(dòng)態(tài)、隨機(jī)、非線性等特點(diǎn),傳統(tǒng)的GM(1,1)模型無法對(duì)其作出準(zhǔn)確的預(yù)測(cè)。利用灰色GM(1,1)模型對(duì)2014年1—5月所查獲的危險(xiǎn)品數(shù)量進(jìn)行計(jì)算、檢驗(yàn),并對(duì)6—8月的危險(xiǎn)品數(shù)量進(jìn)行預(yù)測(cè)。首先建立危險(xiǎn)品數(shù)量的GM(1,1)模型,然后再對(duì)其預(yù)測(cè)值進(jìn)行修正,結(jié)果表明,灰色馬爾科夫模型的平均相對(duì)誤差比灰色預(yù)測(cè)模型的平均相對(duì)誤差減小了25.18%,表明灰色馬爾科夫模型比單一的灰色預(yù)測(cè)模型的精度高,該模型是有效可行的,可為航空公司6—8月將要查獲的危險(xiǎn)品數(shù)量預(yù)測(cè)提供理論基礎(chǔ),以便引起相關(guān)部門的高度重視,并采取相應(yīng)措施以保障旅客安全。
[Abstract]:The quantity of dangerous goods in airport security inspection is dynamic, stochastic and nonlinear, which can not be accurately predicted by the traditional GM (1 / 1) model. The gray GM (1 / 1) model was used to calculate and test the quantity of dangerous goods seized in January-May 2014, and to predict the quantity of dangerous goods in June-August. First, the GM (1K1) model for the quantity of dangerous goods is established, and then the prediction value is modified. The results show that the average relative error of the grey Markov model is 25.18% less than the average relative error of the grey prediction model. It shows that the grey Markov model is more accurate than the single grey prediction model, and the model is effective and feasible. It can provide a theoretical basis for the prediction of the quantity of dangerous goods to be seized by airlines in June-August. In order to attract the attention of relevant departments, and take appropriate measures to ensure passenger safety.
【作者單位】： 中國民航大學(xué)經(jīng)濟(jì)與管理學(xué)院;
【基金】：天津市高等學(xué)校人文社會(huì)科學(xué)研究項(xiàng)目(20102143) 中央高�；究蒲袠I(yè)務(wù)費(fèi)項(xiàng)目(2010D018) 中國民航大學(xué)校科研項(xiàng)目(2011kyE05)
【分類號(hào)】：V328

【相似文獻(xiàn)】

相關(guān)期刊論文 前4條

1 吳晶,黃泰康;馬爾科夫模型及其在藥品經(jīng)濟(jì)預(yù)測(cè)中的應(yīng)用[J];中國藥房;2005年14期

2 覃春喬;陳星;張其成;王衛(wèi)平;;基于馬爾科夫模型的污染物質(zhì)量濃度變化規(guī)律[J];水資源保護(hù);2014年03期

3 王偉民;汪l，

本文編號(hào)：2347072