forecastingcontainerthroughputofqingdaoportwithahybridmodel

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	forecastingcontainerthroughputofqingdaoportwithahybridmodel
	Huang Anqiang 1; Lai Kinkeung 2; Li Yinhua 3; Wang Shouyang4
	2015
发表期刊	journalofsystemsscienceandcomplexity
ISSN	1009-6124
卷号	28 期号:1 页码:105
摘要	This paper proposes a hybrid forecasting method to forecast container throughput of Qingdao Port. To eliminate the influence of outliers, local outlier factor (lof) is extended to detect outliers in time series, and then different dummy variables are constructed to capture the effect of outliers based on domain knowledge. Next, a hybrid forecasting model combining projection pursuit regression (PPR) and genetic programming (GP) algorithm is proposed. Finally, the hybrid model is applied to forecasting container throughput of Qingdao Port and the results show that the proposed method significantly outperforms ANN, SARIMA, and PPR models.
语种	英语
文献类型	期刊论文
条目标识符	http://ir.amss.ac.cn/handle/2S8OKBNM/45247
专题	系统科学研究所
作者单位	1.北京航空航天大学 2.香港城市大学 3.中国科学院 4.中国科学院数学与系统科学研究院
推荐引用方式 GB/T 7714	Huang Anqiang,Lai Kinkeung,Li Yinhua,et al. forecastingcontainerthroughputofqingdaoportwithahybridmodel[J]. journalofsystemsscienceandcomplexity,2015,28(1):105.
APA	Huang Anqiang,Lai Kinkeung,Li Yinhua,&Wang Shouyang.(2015).forecastingcontainerthroughputofqingdaoportwithahybridmodel.journalofsystemsscienceandcomplexity,28(1),105.
MLA	Huang Anqiang,et al."forecastingcontainerthroughputofqingdaoportwithahybridmodel".journalofsystemsscienceandcomplexity 28.1(2015):105.