Article

Analysis and forecasting of port logistics using TEI@I methodology

---

This paper presents an integrated forecasting model based on the TEI@I methodology for forecasting demand for port logistics services – specifically, port container throughput. The model analyzes port logistics time series data and other information in several steps. In the first step, several econometric models are built to forecast the linear segment of port logistics time series. In the second step, a radial basis function neural network is developed to predict the nonlinear segment of the time series. In the third step, the event-study method and expert system techniques are applied to evaluate the effects of economic and other events that may impact demand for port logistics. In the final step, synthetic forecasting results are obtained, based on the integration of predictions from the above three steps. For an illustration, Hong Kong port’s container throughput series is used as a case study. The empirical results show the effectiveness of the TEI@I integrated model for port logistics forecasting.

---

Ketersediaan

Informasi Detail

Judul Seri

Transportation Planning and Technology

No. Panggil

ATC LO WAN a

Penerbit

China : Routledge., 2013

Deskripsi Fisik

20 p.

Bahasa

English

ISBN/ISSN

-

Klasifikasi

LO

Tipe Isi

-

Tipe Media

-

Tipe Pembawa

online resource

Edisi

Vol. 36, No. 8, 685–702

Subjek

Container throughput
Port Logistics
artificial neural network

Info Detail Spesifik

-

Pernyataan Tanggungjawab

Shouyang Wang

Versi lain/terkait

Lampiran Berkas

Komentar

---

Anda harus masuk sebelum memberikan komentar