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  • Open Access

    ARTICLE

    A Deep Reinforcement Learning with Gumbel Distribution Approach for Contention Window Optimization in IEEE 802.11 Networks

    Yi-Hao Tu, Yi-Wei Ma*

    CMC-Computers, Materials & Continua, Vol.84, No.3, pp. 4563-4582, 2025, DOI:10.32604/cmc.2025.066899 - 30 July 2025

    Abstract This study introduces the Smart Exponential-Threshold-Linear with Double Deep Q-learning Network (SETL-DDQN) and an extended Gumbel distribution method, designed to optimize the Contention Window (CW) in IEEE 802.11 networks. Unlike conventional Deep Reinforcement Learning (DRL)-based approaches for CW size adjustment, which often suffer from overestimation bias and limited exploration diversity, leading to suboptimal throughput and collision performance. Our framework integrates the Gumbel distribution and extreme value theory to systematically enhance action selection under varying network conditions. First, SETL adopts a DDQN architecture (SETL-DDQN) to improve Q-value estimation accuracy and enhance training stability. Second, we incorporate a… More >

  • Open Access

    ARTICLE

    Double DQN Method For Botnet Traffic Detection System

    Yutao Hu1, Yuntao Zhao1,*, Yongxin Feng2, Xiangyu Ma1

    CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 509-530, 2024, DOI:10.32604/cmc.2024.042216 - 25 April 2024

    Abstract In the face of the increasingly severe Botnet problem on the Internet, how to effectively detect Botnet traffic in real-time has become a critical problem. Although the existing deep Q network (DQN) algorithm in Deep reinforcement learning can solve the problem of real-time updating, its prediction results are always higher than the actual results. In Botnet traffic detection, although it performs well in the training set, the accuracy rate of predicting traffic is as high as%; however, in the test set, its accuracy has declined, and it is impossible to adjust its prediction strategy on… More >

  • Open Access

    ARTICLE

    B-Spline-Based Curve Fitting to Cam Pitch Curve Using Reinforcement Learning

    Zhiwei Lin1, Tianding Chen1,*, Yingtao Jiang2, Hui Wang1, Shuqin Lin1, Ming Zhu2

    Intelligent Automation & Soft Computing, Vol.36, No.2, pp. 2145-2164, 2023, DOI:10.32604/iasc.2023.035555 - 05 January 2023

    Abstract Directly applying the B-spline interpolation function to process plate cams in a computer numerical control (CNC) system may produce verbose tool-path codes and unsmooth trajectories. This paper is devoted to addressing the problem of B-spline fitting for cam pitch curves. Considering that the B-spline curve needs to meet the motion law of the follower to approximate the pitch curve, we use the radial error to quantify the effects of the fitting B-spline curve and the pitch curve. The problem thus boils down to solving a difficult global optimization problem to find the numbers and positions… More >

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