Automatic Course of Action Generation using Soft Data for Maritime Domain Awareness

被引：3

作者：

Plachkov, Alex ^{[1
]}

Abielmona, Rami ^{[2
]}

Harb, Moufid ^{[2
]}

Falcon, Rafael ^{[2
]}

Inkpen, Diana ^{[1
]}

Groza, Voicu ^{[1
]}

机构：

[1] Univ Ottawa, Sch Elect Engn & Comp Sci, Ottawa, ON K1N 6N5, Canada

[2] Larus Technol Corp, Res & Engn, Ottawa, ON, Canada

来源：

PROCEEDINGS OF THE 2016 GENETIC AND EVOLUTIONARY COMPUTATION CONFERENCE (GECCO'16 COMPANION) | 2016年

关键词：

course of action recommendation; decision support systems; multicriteria decision making; high-level information fusion; soft data;

D O I：

10.1145/2908961.2931678

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Information Fusion (IF) systems have long exploited data provided by hard (physics-based) sensors with the aspiration of making sense of the environment they are monitoring. In recent times, the IF community has recognized the potential of utilizing data generated by people, also known as soft data. In this study, we demonstrate how course of action (CoA) generation, one of the key elements of Level 3 High Level Information Fusion and a vital component for security and defense decision support systems, can be augmented using soft (human-derived) data for improved mission effectiveness. This conceptualization is validated through an elaborate experiment situated in the maritime world. To the best of the authors' knowledge, this is the first study to apply soft data to automatic CoA generation in the maritime domain.

引用

页码：1071 / 1078

页数：8

共 50 条

[21] Automatic Stylized Action Generation in Animation Using Deep Learning
Su, Xiaoyu
Kim, Hyung-Gi
[J]. IEEE Access, 2024, 12 : 188773 - 188786
[22] Big data-driven automatic generation of ship route planning in complex maritime environments
Peng Han
Xiaoxia Yang
[J]. Acta Oceanologica Sinica, 2020, 39 (08) : 113 - 120
[23] Big data-driven automatic generation of ship route planning in complex maritime environments
Peng Han
Xiaoxia Yang
[J]. Acta Oceanologica Sinica, 2020, 39 : 113 - 120
[24] Big data-driven automatic generation of ship route planning in complex maritime environments
Han, Peng
Yang, Xiaoxia
[J]. ACTA OCEANOLOGICA SINICA, 2020, 39 (08) : 113 - 120
[25] Automatic Test Data Generation Using a Genetic Algorithm
Aleb, Nassima
Kechid, Samir
[J]. COMPUTATIONAL SCIENCE AND ITS APPLICATIONS - ICCSA 2013, PT II, 2013, 7972 : 574 - 586
[26] Automatic Test Data Generation Using Particle Systems
Bueno, Paulo M. S.
Wong, W. Eric
Jino, Mario
[J]. APPLIED COMPUTING 2008, VOLS 1-3, 2008, : 809 - +
[27] AUTOMATIC GENERATION OF FPGA HARDWARE ACCELERATORS USING A DOMAIN SPECIFIC LANGUAGE
Menotti, Ricardo
Cardoso, Joao M. P.
Fernandes, Marcio M.
Marques, Eduardo
[J]. FPL: 2009 INTERNATIONAL CONFERENCE ON FIELD PROGRAMMABLE LOGIC AND APPLICATIONS, 2009, : 457 - +
[28] Automatic Parallel Generation of Tetrahedral Grids by Using a Domain Decomposition Approach
Andrae, H.
Gluchshenko, O. N.
Ivanov, E. G.
Kudryavtsev, A. N.
[J]. COMPUTATIONAL MATHEMATICS AND MATHEMATICAL PHYSICS, 2008, 48 (08) : 1367 - 1375
[29] Automatic parallel generation of tetrahedral grids by using a domain decomposition approach
H. Andrä
O. N. Gluchshenko
E. G. Ivanov
A. N. Kudryavtsev
[J]. Computational Mathematics and Mathematical Physics, 2008, 48 : 1367 - 1375
[30] A big data analytics method for the evaluation of maritime traffic safety using automatic identification system data
Ma, Quandang
Tang, Huan
Liu, Cong
Zhang, Mingyang
Zhang, Dingze
Liu, Zhao
Zhang, Liye
[J]. OCEAN & COASTAL MANAGEMENT, 2024, 251

← 1 2 3 4 5 →