analysisofthepredictioncapabilityofwebsearchdatabasedonthehetdcmethodpredictionofthevolumeofdailytourismvisitors

	analysisofthepredictioncapabilityofwebsearchdatabasedonthehetdcmethodpredictionofthevolumeofdailytourismvisitors
	Peng Geng 1; Liu Ying 1; Wang Jiyuan 1; Gu Jifa 2
刊名	journalofsystemsscienceandsystemsengineering
	2017
卷号	26 期号:2 页码:163
ISSN号	1004-3756
英文摘要	Web search query data are obtained to reflect social spots and serve as novel economic indicators. When faced with high-dimensional query data, selecting keywords that have plausible predictive ability and can reduce dimensionality is critical. This paper presents a new integrative method that combines Hurst Exponent (HE) and Time Difference Correlation (TDC) analysis to select keywords with powerful predictive ability. The method is called the HE-TDC screening method and requires keywords with predictive ability to satisfy two characteristics, namely, high correlation and fluctuation memorability similar to the predicting target series. An empirical study is employed to predict the volume of tourism visitors in the Jiuzhai Valley scenic area. The study shows that keywords selected using HE-TDC method produce a model with better robustness and predictive ability.
语种	英语
内容类型	期刊论文
源URL	[http://ir.amss.ac.cn/handle/2S8OKBNM/43223]
专题	中国科学院数学与系统科学研究院
作者单位	1.中国科学院大学 2.中国科学院数学与系统科学研究院
推荐引用方式 GB/T 7714	Peng Geng,Liu Ying,Wang Jiyuan,et al. analysisofthepredictioncapabilityofwebsearchdatabasedonthehetdcmethodpredictionofthevolumeofdailytourismvisitors[J]. journalofsystemsscienceandsystemsengineering,2017,26(2):163.
APA	Peng Geng,Liu Ying,Wang Jiyuan,&Gu Jifa.(2017).analysisofthepredictioncapabilityofwebsearchdatabasedonthehetdcmethodpredictionofthevolumeofdailytourismvisitors.journalofsystemsscienceandsystemsengineering,26(2),163.
MLA	Peng Geng,et al."analysisofthepredictioncapabilityofwebsearchdatabasedonthehetdcmethodpredictionofthevolumeofdailytourismvisitors".journalofsystemsscienceandsystemsengineering 26.2(2017):163.