Modeling Analysis of the Relationship between Adolescent Aerobic Exercise and Obesity Reduction Based on Deep Learning by Peng Mu

“…It also explains the constraint conditions that aerobic exercise has to meet in the reduction of adolescent obesity and introduces particle algorithm to establish a model of optimal aerobic exercise to reduce adolescent obesity. …”
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Improving Secrecy Capacity in the Face of Eavesdropping in SWIPT CIoT Networks With Actor-Critic DRL by Nada Abdel Khalek, Walaa Hamouda

“…We formulate the challenging non-convex optimization problem to maximize secrecy capacity while ensuring spectrum sharing and energy constraints and model the CIoT agent’s decision-making as a model-free Markov decision process (MDP). …”
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Hybrid precoding and power allocation for mmWave NOMA systems based on time delay line arrays by Gangcan SUN, Xinli WU, Wanming HAO, Zhengyu ZHU

“…Specifically,the Dinkelbach method is applied in the outer layer to transform the fractional structure of the objective function in EE optimization into a subtractive structure, and the non-convex objective function is transformed into a convex function by using mathematical tools in the inner layer, and then an iterative algorithm based on alternating optimization (AO) is proposed for power allocation, and finally the solution of the initial problem is obtained by circular iteration in both inner and outer layers. …”
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Leveraging Interactive Evolutionary Computation to Induce Serendipity in Informal Learning by Satoko Inoue, Emmanuel Ayedoun, Hiroshi Takenouchi, Masataka Tokumaru

“…We conducted both numerical simulations and experimental evaluations to assess the effectiveness of our content optimization algorithm and the impact of our approach on inducing serendipity in informal learning environments. …”
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UAV Mission Path Planning Based on Reinforcement Learning in Dynamic Environment by Gui Fu, Yang Gao, Liwen Liu, Mingye Yang, Xinyu Zhu

“…The path planning and optimization of UAV in dynamic environment is studied, and the path planning algorithm and Hungarian algorithm are added. …”
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User Cost Minimization and Load Balancing for Multiple Electric Vehicle Charging Stations Based on Deep Reinforcement Learning by Yongxiang Xia, Zhongyi Cheng, Jiaqi Zhang, Xi Chen

“…In the second stage, we use the DRL algorithm. In the DRL algorithm, we design a novel reward function that enables charging stations to meet user charging demands while minimizing user charging costs and reducing the load gap among distribution networks. …”
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SV-SAE: Layer-Wise Pruning for Autoencoder Based on Link Contributions by Joohong Rheey, Hyunggon Park

“…This paper introduces a layer-wise pruning algorithm specifically for multilayer perceptron-based autoencoders. …”
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YOLO-APDM: Improved YOLOv8 for Road Target Detection in Infrared Images by Song Ling, Xianggong Hong, Yongchao Liu

“…A new algorithm called YOLO-APDM is proposed to address low quality and multi-scale target detection issues in infrared road scenes. …”
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Multiobjective Coverage Control Strategy for Energy-Efficient Wireless Sensor Networks by Hui Zhou, Tian Liang, Chen Xu, Jing Xie

“…A new evolutionary algorithm named Multiobjective free search algorithm (MOFS) is designed for WSN optimization problem based on fitness functions and binary coding schemes. …”
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Deep Q-Learning-Based Resource Management in IRS-Assisted VLC Systems by Ahmed Al Hammadi, Lina Bariah, Sami Muhaidat, Mahmoud Al-Qutayri, Paschalis C. Sofotasios, Merouane Debbah

“…Moreover, the synergy between the MPF and the DQL algorithms is investigated. To this end, we demonstrate that the MPF algorithm maximizes the fairness amongst the users while the DQL algorithm maximizes the overall SE and improves the robustness against the noise. …”
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Multi-Vehicle Object Recognition Method Based on YOLOv7-W by Xin Liu, Jingbin Zhao, Zhi Zhang, Rongxing Wu, Xun Li

“…To improve the matching accuracy of prior frames, the k-means++ clustering algorithm is employed to optimize the prior frame parameters. …”
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Lightweight CNN-Based Visual Perception Method for Assessing Local Environment Complexity of Unmanned Surface Vehicle by Tulin Li, Xiufeng Zhang, Yingbo Huang, Chunxi Yang

“…Subsequently, this identification result can be used as feedback for the heuristic algorithm to optimize and plan the USV’s path. The simulation results indicate that the developed model achieves an 80% reduction in model size while maintaining an accuracy exceeding 90%. …”
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Deep Reinforcement Learning Assisted UAV Path Planning Relying on Cumulative Reward Mode and Region Segmentation by Zhipeng Wang, Soon Xin Ng, Mohammed EI-Hajjar

“…Our proposed region segmentation aims to reduce the probability of DRL agents falling into local optimal trap, while our proposed cumulative reward model takes into account the distance from the node to the destination and the density of obstacles near the node, which solves the problem of sparse training data faced by the DRL algorithms in the path planning task. …”
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Efficient black-box attack with surrogate models and multiple universal adversarial perturbations by Tao Ma, Hong Zhao, Ling Tang, Mingsheng Xue, Jing Liu

“…By combining MUAPs with surrogate models, SMPack effectively overcomes the black-box constraints and improves the efficiency of generating adversarial examples. Additionally, we optimize this process using a Genetic Algorithm (GA), allowing for efficient search of the perturbation space while conserving query budget. …”
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Fusion-Based Localization System Integrating UWB, IMU, and Vision by Zhongliang Deng, Haiming Luo, Xiangchuan Gao, Peijia Liu

“…Among them, visual–inertial odometry (VIO)-based techniques are notably limited by lighting conditions, while ultrawideband (UWB)-based algorithms are highly susceptible to environmental interference. …”
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Anomaly-Based Intrusion Detection System for the Internet of Medical Things by Eichie Franklin, Bernardi Pranggono

“…Our hyperparameter optimization using the Random search algorithm accurately classified normal cases for all six models, with Random Forest (RF) and K-Nearest Neighbors (KNN) performing the best in accuracy. …”
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Energy management strategies for hybrid diesel vehicles by dynamic planning embedded in real-world driving emission model by Yingzhang Wang, Li Zhang, Yang Chen, Chaokai Li, Baocheng Du, Jinlin Han

“…The real-world driving emission model is then embedded into the dynamic planning algorithm using a bi-variate interpolation algorithm on the state-space plane. …”
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European sovereign debt control through reinforcement learning by Tato Khundadze, Willi Semmler, Willi Semmler, Willi Semmler

“…We demonstrate that the Soft Actor-Critic algorithm provides comparable or, in some cases, better solutions to multi-objective macroeconomic optimization problems, in comparison to Nonlinear Model Predictive Control (NMPC) algorithm.…”
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Simultaneously Transmitting and Reflecting Reconfigurable Intelligent Surfaces Empowered Cooperative Rate Splitting with User Relaying by Kangchun Zhao, Yijie Mao, Yuanming Shi

“…Moreover, the proposed low-complexity algorithm dramatically reduces the computational complexity while achieving very close performance to the AO method.…”
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An energy-balanced multi-sensor scheduling scheme for collaborative target tracking in wireless sensor networks by Pengcheng Fu, Hongying Tang, Yongbo Cheng, Baoqing Li, Hanwang Qian, Xiaobing Yuan

“…Then, we put forward a novel energy-balanced sensor nodes scheduling algorithm, Greedy Balance Replace Heuristic Algorithm, to select a near-optimal task sensor set from the candidate sensor node set to balance tracking quality and network lifetime. …”
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