Does Interval Knowledge Sharpen Forecasting Models? Evidence from China's Typical Ports

doi:10.1142/S0219622017500456

CSpace > 系统科学研究所

	Does Interval Knowledge Sharpen Forecasting Models? Evidence from China's Typical Ports
	Huang, Anqiang 1; Lai, Kin Keung 2; Qiao, Han 3; Wang, Shouyang3,4 ; Zhang, Zhenji 1
	2018-03-01
发表期刊	INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
ISSN	0219-6220
卷号	17 期号:2 页码:467-483
摘要	Substantial studies integrating experts' point knowledge with statistical forecasting modes have been implemented to investigate a long-lasting and disputing issue which is whether or not expert knowledge could improve forecasting performance. However, a large body of current forecasting studies neglect the application of experts' interval knowledge where experts are expected to be more competent, considering that humans do much better in fuzzy calculation like interval estimation than in accurate computation like point estimation. To fill in this gap, this paper first proposes a novel forecasting paradigm incorporating interval knowledge generated by a Delphi-based expert system into the SARIMA and SVR models. For validation purposes, the proposed paradigm is applied to several representative seaports from the top three dynamic economic regions in China. The empirical results clearly show that interval knowledge, following the proposed paradigm, significantly improves the forecasting performance. This finding implies that the proposed forecasting paradigm has the good potential to be an effective method for sharpening the statistical models for container throughput forecasting.
关键词	Container throughput forecasting interval knowledge SARIMA SVR
DOI	10.1142/S0219622017500456
语种	英语
资助项目	National Natural Science Foundation of China[71373262] ; National Natural Science Foundation of China[71390330] ; National Natural Science Foundation of China[71390331] ; National Natural Science Foundation of China[71132008] ; National Natural Science Foundation of China[71390334] ; "EC-China Research Network on Integrated Container Supply Chains" Project[612546] ; Fundamental Research Funds for the Central Universities[B15JB00040]
WOS研究方向	Computer Science ; Operations Research & Management Science
WOS类目	Computer Science, Artificial Intelligence ; Computer Science, Information Systems ; Computer Science, Interdisciplinary Applications ; Operations Research & Management Science
WOS记录号	WOS:000428527400002
出版者	WORLD SCIENTIFIC PUBL CO PTE LTD
引用统计
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/30152
专题	系统科学研究所
通讯作者	Qiao, Han
作者单位	1.Beijing Jiaotong Univ, Sch Econ & Management, Beijing 100044, Peoples R China 2.City Univ Hong Kong, Dept Management Sci, Kowloon Tong, Hong Kong, Peoples R China 3.Univ Chinese Acad Sci, Sch Econ & Management, Beijing 100190, Peoples R China 4.Chinese Acad Sci, Acad Math & Syst Sci, Beijing 100190, Peoples R China
推荐引用方式 GB/T 7714	Huang, Anqiang,Lai, Kin Keung,Qiao, Han,et al. Does Interval Knowledge Sharpen Forecasting Models? Evidence from China's Typical Ports[J]. INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING,2018,17(2):467-483.
APA	Huang, Anqiang,Lai, Kin Keung,Qiao, Han,Wang, Shouyang,&Zhang, Zhenji.(2018).Does Interval Knowledge Sharpen Forecasting Models? Evidence from China's Typical Ports.INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING,17(2),467-483.
MLA	Huang, Anqiang,et al."Does Interval Knowledge Sharpen Forecasting Models? Evidence from China's Typical Ports".INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING 17.2(2018):467-483.