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Juan Murillo-Morera, Carlos Castro-Herrera, Javier Arroyo, Ruben Fuentes-Fernandez
Pág. 114 - 137
Today, it is common for software projects to collect measurement data through development processes. With these data, defect prediction software can try to estimate the defect proneness of a software module, with the objective of assisting and guiding so...
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Kimoon Lee, Dongjin Kim, Daewon Chung and Seonho Lee
This study explores optimizing Synthetic Aperture Radar (SAR) satellite constellation scheduling for multi-imaging missions in densely targeted areas using an in-house-developed Modified Dynamic Programming (MDP) algorithm. By employing Mixed-Integer Lin...
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Ziyi Wang, Xinran Li, Luoyang Sun, Haifeng Zhang, Hualin Liu and Jun Wang
Efficient yet sufficient exploration remains a critical challenge in reinforcement learning (RL), especially for Markov Decision Processes (MDPs) with vast action spaces. Previous approaches have commonly involved projecting the original action space int...
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Chen Zhang, Celimuge Wu, Min Lin, Yangfei Lin and William Liu
In the advanced 5G and beyond networks, multi-access edge computing (MEC) is increasingly recognized as a promising technology, offering the dual advantages of reducing energy utilization in cloud data centers while catering to the demands for reliabilit...
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Irina Kochetkova, Kseniia Leonteva, Ibram Ghebrial, Anastasiya Vlaskina, Sofia Burtseva, Anna Kushchazli and Konstantin Samouylov
Fifth-generation (5G) networks provide network slicing capabilities, enabling the deployment of multiple logically isolated network slices on a single infrastructure platform to meet specific requirements of users. This paper focuses on modeling and anal...
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Satoshi Warita and Katsuhide Fujita
Recently, multi-agent systems have become widespread as essential technologies for various practical problems. An essential problem in multi-agent systems is collaborative automating picking and delivery operations in warehouses. The warehouse commission...
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Jiaming Li, Ning Xie and Tingting Zhao
In recent years, with the rapid advancements in Natural Language Processing (NLP) technologies, large models have become widespread. Traditional reinforcement learning algorithms have also started experimenting with language models to optimize training. ...
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Yuhang Zhang and Ming Ni
With the increasing deployment of advanced sensing and measurement devices, the modern distribution system is evolved into a cyber-physical power distribution system (CPPDS). Due to the extensive application of information and communication technology, C...
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Wanli Li, Jiong Li, Ningbo Li, Lei Shao and Mingjie Li
Concerned with the problem of interceptor midcourse guidance trajectory online planning satisfying multiple constraints, an online midcourse guidance trajectory planning method based on deep reinforcement learning (DRL) is proposed. The Markov decision p...
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Marwan Mahmoud and Sami Ben Slama
The Internet of Energy (IoE) is a topic that industry and academics find intriguing and promising, since it can aid in developing technology for smart cities. This study suggests an innovative energy system with peer-to-peer trading and more sophisticate...
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