[1]郑芷雪,郑 列.基于改进灰色马尔可夫模型的实证分析——以上海入境旅客人数预测为例[J].湖北工业大学学报,2020,(1):101-105.
 ZHENG Zhixue,ZHENG Lie.Empirical Analysis Based on Improved Grey Markov Model— Prediction of the Number of Inbound Passengers in Shanghai[J].,2020,(1):101-105.
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基于改进灰色马尔可夫模型的实证分析
——以上海入境旅客人数预测为例
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《湖北工业大学学报》[ISSN:1003-4684/CN:42-1752/Z]

卷:
期数:
2020年第1期
页码:
101-105
栏目:
湖北工业大学学报
出版日期:
2020-02-28

文章信息/Info

Title:
Empirical Analysis Based on Improved Grey Markov Model
— Prediction of the Number of Inbound Passengers in Shanghai
文章编号:
1003-4684(2020)01-0101-05
作者:
郑芷雪郑 列
湖北工业大学理学院,湖北 武汉 430068
Author(s):
ZHENG ZhixueZHENG Lie
School of Sciences, Hubei Univ. of Tech., Wuhan 430068, China
关键词:
GM(11)模型灰色马尔可夫模型入境旅客人数
Keywords:
GM (11) model grey Markov model number of inbound passengers
分类号:
F592.7, F224
文献标志码:
A
摘要:
通过级比检验和马氏检验分别测试上海入境旅客人数的原始数据,原始数据满足级比检验且具有马氏性,然后用传统GM(1,1)模型与初始值校正GM(1,1)模型分别来预测。结果表明,在相对误差、后验差比值与精度三方面对比,初始值校正GM(1,1)模型得到的效果更好。再将初始值校正GM(1,1)模型与加权马尔可夫模型组合成改进灰色马尔可夫模型,结果显示,预测结果的平均相对误差比初始值校正GM(1,1)模型要小,结果更精确。因此,使用改进灰色马尔可夫模型对上海2018—2020年的入境旅客人数预测,结果为:887.63万,900.42万和913.39万人次。
Abstract:
The raw data of Shanghai inbound passengers are tested by the ratio test and the Markov test. The original data satisfy the grade test and have Markov property. The traditional GM (1,1) model and the initial value corrected GM (1, 1) model are predicted separately. The results show that compared with the relative error, posterior difference ratio and accuracy, the initial value correction GM (1,1) model is better. The initial value corrected GM(1,1) model and the weighted Markov model are combined into an improved grey Markov model. The results show that the average relative error of the prediction results is smaller than the initial value correction GM (1,1) model, and the result is more accurate. Therefore, using the improved grey Markov model to predict the number of inbound passengers in Shanghai from 2018 to 2020 yields the following results: 8,876,300, 9,004,200 and 9,313,900. These data can provide reference for Shanghai tourism department and Shanghai tourism enterprises in inbound tourism.

参考文献/References:

[1] 何霞,许宏伟.初值修正灰色预测模型的等价性[J].西华大学学报(自然科学版),2013,32(4):54-57.
[2] 邵红梅,杨建华,兰月新.基于初值修正的组合 GM(1,1)模型及其应用[J].统计与决策,2015(2):89 -90.
[3] 杜晓阳.灰色-加权马尔可夫链的研究及在股市预测中的应用[D].洛阳:河南科技大学,2012.
[4] 茹正亮,杨芝艳,朱文刚,等.加权马尔科夫AR-GARCH-GED模型在降水量中的预测[J].系统工程,2013,31(12):98-102.
[5] 王有文.基于GM(1,l)阳泉旅游人数预测的数学模型[J].山西师范大学学报(自然科学版),2014,28(3):14-17.
[6] 方卫东,怀博.沪深300指数马氏性检验及预测[J].科学技术与工程,2011,11(20):4833-4835.
[7] Zaiwu Gong, Caiqin Chen, Xinming Ge.Risk prediction of low temperature in Nanjing city based on grey weighted Markov model[J].Natural Hazards, 2014, 71 (2):1159-1180.

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备注/Memo

备注/Memo:
[收稿日期] 2019-09-16
[基金项目] 教育部人文社会科学研究一般项目(17YJA790098)
[第一作者] 郑芷雪(1992-), 女, 河南信阳人,湖北工业大学硕士研究生,研究方向为应用统计学
[通信作者] 郑 列(1963-), 男, 湖北英山人,湖北工业大学教授,研究方向为应用数学
更新日期/Last Update: 2020-04-11