Výsledky vyhledávání - Advanced deep- Q network algorithm

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  1. 1

    Automated DoS Penetration Testing Using Deep Q Learning Network-Quantile Regression Deep Q Learning Network Algorithms Autor Alhamed, Mariam, Rahman, M M Hafizur

    ISSN: 2158-107X, 2156-5570
    Vydáno: West Yorkshire Science and Information (SAI) Organization Limited 2025
    “… As a result of this algorithm, an attack tree is generated, paths within the attack graph are searched for, and a deep-first search method is used to create a transfer matrix…”
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  2. 2

    Impact of energy storage devices on microgrid frequency performance: A robust DQN based grade-2 fuzzy cascaded controller Autor Sahu, Prakash Chandra, Jena, Smitasree, Mohapatra, Srikanta, Debdas, Subhra

    ISSN: 2772-6711, 2772-6711
    Vydáno: Elsevier Ltd 01.12.2023
    Vydáno v e-Prime (01.12.2023)
    “…•A microgrid is modeled by integrating various distributed power sources (DG) such as solar power stations (SPS), micro turbine (MT), wind power stations (WPS)…”
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  3. 3

    Traffic prediction and load balancing routing algorithm based on deep Q-network for SD-IoT Autor Ding, Qiao, Li, Nanyu, Ding, Heng, Wang, Jian, Li, Tao, Chen, Yongqing, Xian, Yantuan, Chen, Junyang

    ISSN: 1474-0346
    Vydáno: Elsevier Ltd 01.11.2025
    Vydáno v Advanced engineering informatics (01.11.2025)
    “…) networks are encountering increasingly severe challenges in routing and load balancing. To address this, this paper proposes an intelligent load-balancing routing algorithm based on deep Q-network (LBR-DQN…”
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  4. 4

    An advanced deep reinforcement learning algorithm for three-layer D2D-edge-cloud computing architecture for efficient task offloading in the Internet of Things Autor Moghaddasi, Komeil, Rajabi, Shakiba, Gharehchopogh, Farhad Soleimanian, Ghaffari, Ali

    ISSN: 2210-5379
    Vydáno: Elsevier Inc 01.09.2024
    “…), an advanced Deep Reinforcement Learning (DRL) algorithm. This algorithm utilizes advanced neural networks to optimize task offloading in the three-tier framework…”
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  5. 5

    Design of Big Data Task Scheduling Optimization Algorithm Based on Improved Deep Q-Network Autor Chen, Fu, Wu, Chunyi

    ISSN: 2158-107X, 2156-5570
    Vydáno: West Yorkshire Science and Information (SAI) Organization Limited 2024
    “… To overcome this, a scheduling model based on Markov decision process is proposed. The deep Q-network algorithm is used for directed acyclic graph task scheduling…”
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  6. 6

    Research on the Local Path Planning for Mobile Robots based on PRO-Dueling Deep Q-Network (DQN) Algorithm Autor Zhang, Yaoyu, Li, Caihong, Zhang, Guosheng, Zhou, Ruihong, Liang, Zhenying

    ISSN: 2158-107X, 2156-5570
    Vydáno: West Yorkshire Science and Information (SAI) Organization Limited 2023
    “…This paper proposes a Pro-Dueling DQN algorithm to solve the problems of slow convergence speed and waste of effective experience of the traditional DQN (Deep Q-Network…”
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  7. 7

    An empirical study of the naïve REINFORCE algorithm for predictive maintenance Autor Siraskar, Rajesh, Kumar, Satish, Patil, Shruti, Bongale, Arunkumar, Kotecha, Ketan, Kulkarni, Ambarish

    ISSN: 3004-9261, 2523-3963, 3004-9261, 2523-3971
    Vydáno: Cham Springer International Publishing 08.03.2025
    Vydáno v Discover applied sciences (08.03.2025)
    “… However, these algorithms are extremely sensitive to hyperparameter tuning and network architecture, and this is where automated RL frameworks (AutoRL…”
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  8. 8

    FAQ: A Fuzzy-Logic-Assisted Q Learning Model for Resource Allocation in 6G V2X Autor Zhang, Minglong, Dou, Yi, Marojevic, Vuk, Chong, Peter Han Joo, Chan, Henry C. B.

    ISSN: 2327-4662, 2327-4662
    Vydáno: Piscataway IEEE 15.01.2024
    Vydáno v IEEE internet of things journal (15.01.2024)
    “…) communications in the six generation (6G) cellular networks. Cellular V2X (C-V2X) communications empower advanced applications but at the same time bring unprecedented…”
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  9. 9

    Simulating multi‐exit evacuation using deep reinforcement learning Autor Xu, Dong, Huang, Xiao, Mango, Joseph, Li, Xiang, Li, Zhenlong

    ISSN: 1361-1682, 1467-9671
    Vydáno: Oxford Blackwell Publishing Ltd 01.06.2021
    Vydáno v Transactions in GIS (01.06.2021)
    “… MultiExit‐DRL, which involves a deep neural network (DNN) framework to facilitate state‐to‐action mapping. The DNN framework applies Rainbow Deep Q…”
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  10. 10

    Two-Stage WECC Composite Load Modeling: A Double Deep Q-Learning Networks Approach Autor Wang, Xinan, Wang, Yishen, Shi, Di, Wang, Jianhui, Wang, Zhiwei

    ISSN: 1949-3053, 1949-3061
    Vydáno: Piscataway IEEE 01.09.2020
    Vydáno v IEEE transactions on smart grid (01.09.2020)
    “… Enabled by the wide deployment of PMUs and advanced deep learning algorithms, proposed here is a double deep Q-learning network (DDQN…”
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  11. 11

    Waste Objects Segregation Using Deep Reinforcement Learning with Deep Q Networks Autor Khan, Nida, Kulkarni, Kunal, Mahale, Yashashree, Kolhar, Shrikrishna, Mahajan, Smita

    ISSN: 1633-1311, 2116-7125
    Vydáno: Edmonton International Information and Engineering Technology Association (IIETA) 01.12.2024
    “… The Deep Q Network model proposed achieved an accuracy of approximately 73%. By employing DQN, an advanced reinforcement learning algorithm, the system ensures improved…”
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  12. 12

    Fast or Slow: An Autonomous Speed Control Approach for UAV-assisted IoT Data Collection Networks Autor Chu, Nam H., Hoang, Dinh Thai, Nguyen, Diep N., Huynh, Nguyen Van, Dutkiewicz, Eryk

    ISSN: 1558-2612
    Vydáno: IEEE 01.01.2021
    “… In this way, the Q-learning algorithm can be adopted to obtain the optimal speed control policy for the UAV…”
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  13. 13

    Deep reinforcement learning for photovoltaic performance ratio estimation and accurate degradation stage diagnosis based on precise RS-RP evaluation Autor Salehpour, Sherko, Eskandari, Aref, Nedaei, Amir, Aghaei, Mohammadreza

    ISSN: 2590-1230, 2590-1230
    Vydáno: Elsevier B.V 01.12.2025
    Vydáno v Results in engineering (01.12.2025)
    “…) algorithms, namely Deep Q-Network (DQN), and soft actor-critic (SAC), to (i) detect and distinguish degradation conditions using a binary classification model and (ii…”
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  14. 14

    An exploratory study on intelligent active cell balancing of electric vehicle battery management and performance using machine learning algorithms Autor Rao, Veeranki Srinivasa, Sajja, Guna Sekhar, Manur, Vishwaraj B, Arandhakar, Sairaj, Krishna, V.B. Murali

    ISSN: 2590-1230, 2590-1230
    Vydáno: Elsevier B.V 01.03.2025
    Vydáno v Results in engineering (01.03.2025)
    “…•PA-RNN, Deep-Q, AQN, ADNN & AC enhance SoC accuracy and control.•Automotive Controllers are EV-specific for improved performance…”
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    Optimization of cache-enabled opportunistic interference alignment wireless networks: A big data deep reinforcement learning approach Autor Ying He, Chengchao Liang, Yu, F. Richard, Nan Zhao, Hongxi Yin

    ISSN: 1938-1883
    Vydáno: IEEE 01.05.2017
    “… Deep reinforcement learning is an advanced reinforcement learning algorithm that uses deep Q network to approximate the Q value-action function…”
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  16. 16

    Discrete Space Deep Reinforcement Learning Algorithm Based on Support Vector Machine Recursive Feature Elimination Autor Kim, Chayoung

    ISSN: 2073-8994, 2073-8994
    Vydáno: Basel MDPI AG 01.08.2024
    Vydáno v Symmetry (Basel) (01.08.2024)
    “…) developed from the double deep Q-network (DDQN) in deep reinforcement learning (DRL) has become a standard…”
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  17. 17

    Multi-Channel Opportunistic Access for Heterogeneous Networks Based on Deep Reinforcement Learning Autor Ye, Xiaowen, Yu, Yiding, Fu, Liqun

    ISSN: 1536-1276, 1558-2248
    Vydáno: New York IEEE 01.02.2022
    “…This paper investigates a new medium access control (MAC) protocol for multi-channel heterogeneous networks (HetNets…”
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  18. 18

    Deep-Reinforcement-Learning-Based Optimization for Cache-Enabled Opportunistic Interference Alignment Wireless Networks Autor Ying He, Zheng Zhang, Yu, F. Richard, Nan Zhao, Hongxi Yin, Leung, Victor C. M.

    ISSN: 0018-9545, 1939-9359
    Vydáno: New York IEEE 01.11.2017
    “…, which is an advanced reinforcement learning algorithm that uses a deep Q network to approximate the Q value-action function…”
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  19. 19

    Advanced EEG Signal Processing and Deep Q-Learning for Accurate Student Attention Monitoring Autor Ur Rehman, Asad, Ul Eman, Noor, Ullah, Farhan, Cacciagrano, Diletta, Mostarda, Leonardo, Raza, Nabeel

    ISSN: 2169-3536, 2169-3536
    Vydáno: IEEE 01.01.2025
    Vydáno v IEEE access (01.01.2025)
    “… This study introduces an enhanced approach that leverages advanced data preprocessing techniques and a Double Deep Q-Network (DDQN…”
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  20. 20

    EdDSA Based Network Data Authentication and Intrusion Detection System Using QDQN‐DPER With Hippopotamus Optimization Autor Babu, B. V. Satish, Bikku, Thulasi, Ponkumar, D. David Neels, Uma Maheswaran, S. K., Maguluri, Lakshmana Phaneendra

    ISSN: 0143-2087, 1099-1514
    Vydáno: Hoboken, USA John Wiley & Sons, Inc 01.09.2025
    “…‐curve digital signature algorithm (EdDSA) and quantum deep Q‐learning with distributed prioritized experience replay (QDQN‐DPER…”
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