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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Shih-Liang Chao Ya-Lan Lin |
| Copyright Year | 2010 |
| Description | Author affiliation: Dept. of Shipping & Transp. Manage., Nat. Taiwan Ocean Univ., Keelung, Taiwan (Shih-Liang Chao; Ya-Lan Lin) |
| Abstract | Container traffic passing through terminals has increased dramatically. The massive flows of trucks and containers typically cause traffic jams when processing efficiency at a gate is insufficient. Therefore, automatic gate systems that recognize container numbers and truck license plates are needed in container terminals. However, several systems, such as radio frequency identification (RFID) and optical character recognition (OCR), can be used for gate automation. How to choose a suitable system is an important planning problem for terminal operators. This study identified the determinants influencing terminal operators while choosing an automated gate system. An objective structure was hierarchically constructed by exploratory factor analysis (EFA) to aid decision-making when choosing an automated gate system. An empirical study based on a dedicated terminal at the Keelung Port was conducted to assess the suitability of the RFID and OCR systems. The fuzzy analytical hierarchy process was applied to calculate the relative weights of criteria and the alternatives. Analytical results demonstrate that the RFID system is the most suitable system for the Keelung Port terminal. |
| Starting Page | 1 |
| Ending Page | 7 |
| File Size | 133997 |
| Page Count | 7 |
| File Format | |
| ISBN | 9789623676960 |
| e-ISBN | 9789623676960 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-10-06 |
| Publisher Place | China |
| Access Restriction | Subscribed |
| Rights Holder | Hong Kong Polytechnic Uni |
| Subject Keyword | Automation Liner shipping Container terminal Loading Containers Logic gates RFID Optical character recognition software Security Fuzzy AHP Radiofrequency identification OCR |
| Content Type | Text |
| Resource Type | Article |
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