Does Interval Knowledge Sharpen Forecasting Models? Evidence from China's Typical Ports
Huang, Anqiang1; Lai, Kin Keung2; Qiao, Han3; Wang, Shouyang3,4; Zhang, Zhenji1
刊名INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING
2018-03-01
卷号17期号:2页码:467-483
关键词Container throughput forecasting interval knowledge SARIMA SVR
ISSN号0219-6220
DOI10.1142/S0219622017500456
英文摘要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.
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
语种英语
出版者WORLD SCIENTIFIC PUBL CO PTE LTD
WOS记录号WOS:000428527400002
内容类型期刊论文
源URL[http://ir.amss.ac.cn/handle/2S8OKBNM/30151]  
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.
个性服务
查看访问统计
相关权益政策
暂无数据
收藏/分享
所有评论 (0)
暂无评论
 

除非特别说明,本系统中所有内容都受版权保护,并保留所有权利。


©版权所有 ©2017 CSpace - Powered by CSpace