Energy Efficiency Maximization in RISs-Assisted UAVs-Based Edge Computing Network Using Deep Reinforcement Learning by Chuanwen Luo, Jian Zhang, Jianxiong Guo, Yi Hong, Zhibo Chen, Shuyang Gu

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Optimizing Pre-Trained Models for Medical Dataset Classification with a Fine-Tuning Approach by N. Kumar, T. Christopher

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A Secure and Reliable Fog-Enabled Architecture Using Blockchain With Functional Biased Elliptic Curve Cryptography Algorithm for Healthcare Services by charu awasthi, Satya Prakash, Prashant Kumar Mishra

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Is GPT-4 fair? An empirical analysis in automatic short answer grading by Luiz Rodrigues, Cleon Xavier, Newarney Costa, Dragan Gasevic, Rafael Ferreira Mello

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Noise Robustness of Quantum Relaxation for Combinatorial Optimization by Kentaro Tamura, Yohichi Suzuki, Rudy Raymond, C. Hiroshi Watanabe, Yuki Sato, Ruho Kondo, Michihiko Sugawara, Naoki Yamamoto

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Optimizing ML models for cybercrime detection: balancing performance, energy consumption, and carbon footprint through multi-objective optimization by Romil Rawat

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Optimal sizing and siting of energy storage systems based on power grid vulnerability analysis: a trilevel optimization model by Zhenghui Zhao, Yingying Shang, Buyang Qi, Yang Wang, Qian Zhang

“…The middle-level employs an improved particle swarm optimization algorithm to determine the optimal capacity and power configuration of BESS, aiming to maximize its equivalent annual revenue. …”
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A Deep-Layered Water Flow Optimizer for Global Continuous Optimization Problems and Parameter Estimation of Solar Photovoltaic Models by Zhentao Tang, Kaiyu Wang, Mingxin Zhu, Yongxuan Yao, Lan Zhuang, Huiqin Chen, Jing Li, Li Yan, Shangce Gao

“…In the experimental section, we compare DWFO with nine state-of-the-art algorithms on the IEEE Congress on Evolutionary Computation 2017 (CEC2017) benchmark functions and the CEC2011 real-world optimization problems. …”
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Hierarchical guided manta ray foraging optimization for global continuous optimization problems and parameter estimation of solar photovoltaic models by Zhentao Tang, Kaiyu Wang, Lan Zhuang, Mingxin Zhu, Yongxuan Yao, Huiqin Chen, Jing Li, Xiaoxiang Wu, Shangce Gao

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Configuration optimization for a plate-fin heat exchanger combining Taguchi method and multi-objective grey wolf optimizer by Zhe Xu, Changyin Zhao, Xin Ning, Mengyao Qin, Zhen Zhang, Fuquan Nie

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Modeling of 3 SAT discrete Hopfield neural network optimization using genetic algorithm optimized K-modes clustering by Xiaojun Xie, Saratha Sathasivam, Hong Ma

“…Subsequently, the paper presented a DHNN-3SAT model optimized by genetic algorithms combined with K-modes clustering. …”
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Using Multiple Criteria Optimization and Two-Stage Genetic Algorithms to Select a Population Management Strategy with Optimized Reliability by Jessica L. Chapman, Lu Lu, Christine M. Anderson-Cook

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Optimizing Fractional Differential Equation Solutions with Novel Müntz Space Basis Functions by Asrin shekh, Kamaran Jamal Hamad, salm saeed mahmood

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A state-of-the-art review of soft computing-based monitoring and control in the machining of hard alloys by Lokesh Kumar, Ashish Goyal, Vimal Kumar Pathak, Abhijit Bhowmik

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Optimizing diabetic retinopathy detection with electric fish algorithm and bilinear convolutional networks by Udayaraju Pamula, Venkateswararao Pulipati, G. Vijaya Suresh, M. V. Jagannatha Reddy, Anil Kumar Bondala, Srihari Varma Mantena, Ramesh Vatambeti

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Intelligent data analysis in edge computing with large language models: applications, challenges, and future directions by Xuanzheng Wang, Zhipeng Xu, Xingfei Sui

“…This survey explores the intersection of these two domains, specifically focusing on the adaptation and optimization of LLMs for data analysis tasks in edge computing environments. …”
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Optimizing Fairness and Spectral Efficiency With Shapley-Based User Prioritization in Semantic Communication by Moirangthem Tiken Singh, Adnan Arif, Rabinder Kumar Prasad, Bikramjit Choudhury, Chandan Kalita, Sikdar Md. S. Askari

“…The Shapley-based approach outperforms established methods, including the Hungarian algorithm, reinforcement learning algorithms like Deep Q-Network (DQN) and Proximal Policy Optimization (PPO), as well as conventional 4G and 5G resource allocation strategies. …”
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Application of 5G + edge computing technology in intelligent monitoring construction of electricity business office by Wei Cui, Junwei Li, Wei Ge, Bo Zhang, Tianwei Liu

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Client grouping and time-sharing scheduling for asynchronous federated learning in heterogeneous edge computing environment by Qianpiao MA, Qingmin JIA, Jianchun LIU, Hongli XU, Renchao XIE, Tao HUANG

“…To overcome the three key challenges of federated learning in heterogeneous edge computing, i.e., edge heterogeneity, data Non-IID, and communication resource constraints, a grouping asynchronous federated learning (FedGA) mechanism was proposed.Edge nodes were divided into multiple groups, each of which performed global updated asynchronously with the global model, while edge nodes within a group communicate with the parameter server through time-sharing communication.Theoretical analysis established a quantitative relationship between the convergence bound of FedGA and the data distribution among the groups.A time-sharing scheduling magic mirror method (MMM) was proposed to optimize the completion time of a single round of model updating within a group.Based on both the theoretical analysis for FedGA and MMM, an effective grouping algorithm was designed for minimizing the overall training completion time.Experimental results demonstrate that the proposed FedGA and MMM can reduce model training time by 30.1%～87.4% compared to the existing state-of-the-art methods.…”
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Hierarchical Reinforcement Learning for Multi-Layer Multi-Service Non-Terrestrial Vehicular Edge Computing by Swapnil Sadashiv Shinde, Daniele Tarchi

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