Faculty of Geodesy and Geomatics Engineering, K.N. Toosi University
of Technology, Tehran, Iran
Mahdi Panahi
Division of Smart Regional Innovation, Kangwon National University, 1 Gangwondaehak-gil, Chuncheon-si, Gangwon-do, 24341, Republic of Korea
Geoscience Platform Division, Korea Institute of Geoscience and Mineral Resources (KIGAM), 124 Gwahak-ro, Yuseong-gu, Daejeon, 34132, Republic of Korea
Geoscience Platform Division, Korea Institute of Geoscience and Mineral Resources (KIGAM), 124 Gwahak-ro, Yuseong-gu, Daejeon, 34132, Republic of Korea
Department of Geophysical Exploration, Korea University of Science and Technology, 217 Gajeong-ro, Yuseong-gu, Daejeon, 305-350, Republic of Korea
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1,997
1,026
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3,126
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PDF: 1,026
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Total: 3,126
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EndNote: 147
Views and downloads (calculated since 09 Nov 2020)
Cumulative views and downloads
(calculated since 09 Nov 2020)
Total article views: 2,474 (including HTML, PDF, and XML)
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1,620
764
90
2,474
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HTML: 1,620
PDF: 764
XML: 90
Total: 2,474
BibTeX: 123
EndNote: 133
Views and downloads (calculated since 15 Nov 2021)
Cumulative views and downloads
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Total article views: 652 (including HTML, PDF, and XML)
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377
262
13
652
16
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HTML: 377
PDF: 262
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Total: 652
BibTeX: 16
EndNote: 14
Views and downloads (calculated since 09 Nov 2020)
Cumulative views and downloads
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Viewed (geographical distribution)
Total article views: 3,126 (including HTML, PDF, and XML)
Thereof 2,992 with geography defined
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Total article views: 2,474 (including HTML, PDF, and XML)
Thereof 2,385 with geography defined
and 89 with unknown origin.
Total article views: 652 (including HTML, PDF, and XML)
Thereof 607 with geography defined
and 45 with unknown origin.
Task allocation under uncertain conditions is a key problem for agents attempting to achieve harmony in disaster environments. This paper presents an agent-based simulation to investigate task allocation considering appropriate spatial strategies to manage uncertainty in urban search and rescue (USAR) operations.
Task allocation under uncertain conditions is a key problem for agents attempting to achieve...
