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  • Search: subject:"Deep Learning Model"
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Year of publication
Subject
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Deep learning model 3 Alternative marine power 2 Busan new port 2 Long-short-term memory model 2 Seaport 2 Supply and demand 2 electrical power consumption 2 China 1 Early warning 1 Early warning system 1 Electric power industry 1 Elektrizitätswirtschaft 1 Energiekonsum 1 Energy consumption 1 Erdölindustrie 1 Erdölvorkommen 1 Frühwarnsystem 1 Hafen 1 National security 1 Nationale Sicherheit 1 Oil industry 1 Petroleum resources 1 Petroleum security 1 Port 1 Scenario projection 1 Variable weight 1
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Online availability
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Free 3 CC license 2
Type of publication
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Article 3
Type of publication (narrower categories)
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Article in journal 2 Aufsatz in Zeitschrift 2 Article 1
Language
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English 3
Author
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An, Seunghyun 2 Kim, GeunSub 2 Lee, Gunwoo 2 Lee, Joowon 2 Dong, Juan 1 Li, Qi 1 Luo, Ting 1 Zheng, Minggui 1
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Published in...
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Asian Journal of Shipping and Logistics (AJSL) 1 Energy strategy reviews 1 The Asian Journal of Shipping and Logistics 1
Source
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ECONIS (ZBW) 2 EconStor 1
Showing 1 - 3 of 3
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National security evaluation and early warning system of petroleum resources in China
Li, Qi; Zheng, Minggui; Dong, Juan; Luo, Ting - In: Energy strategy reviews 62 (2025), pp. 1-22
Amidst the constraints of carbon peaking and carbon neutrality goals (dual carbon) and high import dependence, safeguarding China's petroleum security faces intensified challenges. This study constructs a dynamic weight evaluation framework integrating four dimensions: "Availability",...
Persistent link: https://www.econbiz.de/10015593468
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Forecasting future electric power consumption in Busan New Port using a deep learning model
Kim, GeunSub; Lee, Gunwoo; An, Seunghyun; Lee, Joowon - In: Asian Journal of Shipping and Logistics (AJSL) 39 (2023) 2, pp. 78-93
As smart and environmentally friendly technologies and equipment are introduced in the sea port industry, electric power consumption is expected to rapidly increase. However, there is a paucity of research on the creation of electric power management plans, specifically in relation to electric...
Persistent link: https://www.econbiz.de/10015471106
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Cover Image
Forecasting future electric power consumption in Busan New Port using a deep learning model
Kim, GeunSub; Lee, Gunwoo; An, Seunghyun; Lee, Joowon - In: The Asian Journal of Shipping and Logistics 39 (2023) 2, pp. 78-93
As smart and environmentally friendly technologies and equipment are introduced in the sea port industry, electric power consumption is expected to rapidly increase. However, there is a paucity of research on the creation of electric power management plans, specifically in relation to electric...
Persistent link: https://www.econbiz.de/10014281602
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