NDLI: A TEI@I-Based Integrated Framework for Port Logistics Forecasting

Content Provider	IEEE Xplore Digital Library
Author	Xin Tian Xiaoshan Lu Xingmai Deng
Copyright Year	2009
Abstract	This paper proposes an integrated forecasting framework based on the TEI@I methodology for port logistics forecasting. The framework analyzes and forecasts the port logistics time series data with a few steps. Firstly, census X12 seasonal adjustment method is applied to decompose the time series to several components: trend and cycle component, irregular component and seasonal component. Secondly, econometrical models and artificial neural network techniques are used to forecast the trend and cycle component and irregular component respectively. Thirdly, event-study method and expert system technique are applied to evaluate the effects of economic and other events that may impact port logistics. Finally, synthetic forecasting results are obtained based on the integration of the predictions from three above steps. For illustration, Shenzhen port’ container throughout series is used for a case study. The empirical results show the effectiveness of the TEI@I-based integrated model for port logistics forecasting.
Starting Page	293
Ending Page	296
File Size	274811
Page Count	4
File Format	PDF
ISBN	9780769537054
DOI	10.1109/BIFE.2009.74
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-07-24
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	TEI@I methodology forecasting Predictive models Containers Conference management Financial management Throughput port logistics container throughput Technology management Economic forecasting Technology forecasting Econometrics Logistics back-propagation neural network
Content Type	Text
Resource Type	Article

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