Machine Learning to Improve Situational Awareness in Beyond Visual Range Air Combat-Reference-Cited by-同舟云学术

Machine Learning to Improve Situational Awareness in Beyond Visual Range Air Combat

Published:2022-08 Issue:8 Volume:20 Page:2039-2045
ISSN:1548-0992
Container-title:IEEE Latin America Transactions
language:
Short-container-title:IEEE Latin Am. Trans.

Author:

Dantas Joao P. A.¹^ORCID,Maximo Marcos R. O. A.²^ORCID,Costa Andre N.¹^ORCID,Geraldo Diego¹^ORCID,Yoneyama Takashi³^ORCID

Affiliation:

1. Decision Support Systems Subdivision, Institute for Advanced Studies, Sao Jose dos Campos - Sao Paulo, 12228-001, Brazil

2. Autonomous Computational System Lab (LAB-SCA), Computer Science Division, Aeronautics Institute of Technology, Sao Jose dos Campos - Sao Paulo, 12228-900, Brazil

3. Electronic Engineering Division, Aeronautics Institute of Technology, Sao Jose dos Campos - Sao Paulo, 12228-900, Brazil

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,General Computer Science

Link

http://xplorestaging.ieee.org/ielx7/9907/9853223/09853232.pdf?arnumber=9853232

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1. AsaPy: A Python Library for Aerospace Simulation Analysis;Proceedings of the 38th ACM SIGSIM Conference on Principles of Advanced Discrete Simulation;2024-06-24

2. Situation Awareness in AI-Based Technologies and Multimodal Systems: Architectures, Challenges and Applications;IEEE Access;2024

3. Multicriteria Game Approach to Air-to-Air Combat Tactical Decisions for Multiple UAVs;Journal of Systems Engineering and Electronics;2023-12

4. Autonomous Agent for Beyond Visual Range Air Combat: A Deep Reinforcement Learning Approach;ACM SIGSIM Conference on Principles of Advanced Discrete Simulation;2023-06-21

5. Supervised Machine Learning for Effective Missile Launch Based on Beyond Visual Range Air Combat Simulations;2022 Winter Simulation Conference (WSC);2022-12-11