Retracted: Emergency Decision Support System for Container Logistics Safety Based on Image Processor

Zhu, Wenying; Kamruzzaman, M. M.; Sun, Xia; Zhang, Xiaheng

doi:10.1109/access.2020.3020514

Cited by 2 publications

(2 citation statements)

References 15 publications

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“…(1) Accept consignment applications and conclude multimodal transport contracts (2) Issuance, pickup, and delivery of containers (3) Export declaration (4) Packing of goods and receiving goods (5) Booking space and arranging cargo delivery (6) Apply for insurance (7) Issuing a multimodal transport bill of lading to organize and complete the entire transportation of goods (8) Customs business during transportation (9) Delivery of goods (10) Handling of freight accidents Among them, the business has better requirements for the overall system design mainly in 1, 4, 6, and 3. It is explained as follows:…”

Section: Container Multimodal Cooperative Transportationmentioning

confidence: 99%

“…Zhu's article draws on the research results at home and abroad, introduces an image processing system, uses mathematical modeling optimization methods, and summary induction methods to establish an image processor-based container multimodal logistics safety emergency decision support system research model. e combination of qualitative analysis and quantitative analysis, based on theory, early warning management methods, and emergency decision-making system, made in-depth thinking on the image-based container multimodal transport logistics safety emergency decision support system [7]. ere are still many problems encountered in the actual operation process, such as the coordinated deployment of vehicles, the coordination of multiple ports, and the different modes of operation.…”

Section: Introductionmentioning

confidence: 99%

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Container Multimodal Cooperative Transportation Management Information System Based on Artificial Intelligence Technology

Wang¹,

2021

Mathematical Problems in Engineering

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Artificial intelligence is a branch of computer science, which includes natural language, intelligent processing, and professional methods. Since the birth of artificial intelligence, the technology and application fields have continued to grow, and the application fields have also continued to expand. This article aims to study the application of artificial intelligence technology in the management information system of container multimodal transportation and to provide convenient and efficient operation methods for container multimodal transportation. This paper proposes the C-means clustering method. Through the research and development of the terminal management system, it has achieved great success in automation, intelligent planning, and integrated management. At the same time, the EDI system is adopted, which mainly uses the combination of GPS and GIS information platform Internet network technology. Therefore, when evaluating the operation of the multimodal transport virtual container under the control of coproduction, the DEA method is used to operate the multimodal virtual container. The situation is analyzed and evaluated, and the multimodal transport virtual container is determined through investment. The experimental results of this article show that the artificial intelligence system achieves the most efficient multimodal transport management with the most efficient system model, combined with the leading container multimodal transport virtual enterprise, to provide the best way of the management process for the development of the multimodal transport management information system. The intact rate of container cargo during transportation is as high as 99.7%.

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Section: Container Multimodal Cooperative Transportationmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%