Optimal Configuration of Multi-microgrid System with Multi-agent Joint Investment Based on Stackelberg Game by Ruiyuan PAN, Zhong TANG, Chenhao SHI, Minjie WEI, An LI, Weiyang DAI

“…Then, a Stackelberg game model is built to minimize the payoff function of the multi-microgrid system and maximize the revenue of distribution networks separately. In addition, an algorithm combining the adaptive genetic algorithm and particle swarm optimization is proposed to solve the optimal configuration of distributed power in the multi-microgrid system. …”
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Fusion of Visible and Infrared Images Using a Reinforcement Learning System Based on Fuzzy Logic and Convolution Optimized with Wild Horse Algorithm by Mahvash Zarimeidani, Amir Amirabadi, Nasrin Amiri, Iman Ahanian, Siavash Es’haghi

“…This hybrid reinforcement learning system was optimized using algorithms including wild horse optimization (WHO), genetic algorithm (GA), and particle swarm optimization (PSO) to improve specific fusion metrics such as image correlation, similarity coefficient, image entropy, and signal-to-noise ratio. …”
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Research on cooperative control strategy for high efficiency and energy saving in virtually coupled train sets based on two-layer optimization by JIANG Sidun, FENG Jianghua, ZHANG Zhengfang, SHI Ke, LUO Qinyang

“…The lower layer concentrates on energy-saving optimization, establishing an objective function for energy saving and utilizing a multi-objective particle swarm algorithm to optimize cruising curves. …”
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Optimized ensemble learning for non-destructive avocado ripeness classification by Panudech Tipauksorn, Prasert Luekhong, Minoru Okada, Jutturit Thongpron, Chokemongkol Nadee, Krisda Yingkayun

“…Five machine learning models Random Forest, Decision Tree, XGBoost, Gradient Boosting, and Gaussian Mixture Model were trained separately and then merged into an ensemble. Four algorithms were used to optimize the model weight distribution: Bayesian Optimisation, Differential Evolution, Particle Swarm Optimisation, and Grid Search. …”
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Optimizing Outdoor Micro-Space Design for Prolonged Activity Duration: A Study Integrating Rough Set Theory and the PSO-SVR Algorithm by Jingwen Tian, Zimo Chen, Lingling Yuan, Hongtao Zhou

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Optimizing LoRaWAN Gateway Placement in Urban Environments: A Hybrid PSO-DE Algorithm Validated via HTZ Simulations by Kanar Alaa Al-Sammak, Sama Hussein Al-Gburi, Ion Marghescu, Ana-Maria Claudia Drăgulinescu, Cristina Marghescu, Alexandru Martian, Nayef A. M. Alduais, Nawar Alaa Hussein Al-Sammak

“…This study investigates how to optimize the placement of LoRaWAN gateways by using a combination of Particle Swarm Optimization (PSO) and Differential Evolution (DE). …”
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Optimized deep neural network architectures for energy consumption and PV production forecasting by Eghbal Hosseini, Barzan Saeedpour, Mohsen Banaei, Razgar Ebrahimy

“…This paper introduces a novel hybrid optimization approach that integrates Genetic Algorithms (GA) and Particle Swarm Optimization (PSO) to enhance the DNN architecture for more accurate energy forecasting. …”
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Allocation of Interline Power Flow Controller-Based Congestion Management in Deregulated Power System by Muhammad Safdar Sial, Qinghua Fu, Talles Vianna Brugni

“…By examining the obtained results, the performance of the proposed algorithm is better than the Genetic Algorithm (GA) and Particle Swarm Optimization (PSO) algorithms. …”
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An innovative maximum power point tracking for photovoltaic systems operating under partially shaded conditions using Grey Wolf Optimization algorithm by Muhannad J. Alshareef

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CSO Intelligent Optimization of Drag Torque Parameters of Wet Brakes Based on the SSA-BP Approximate Model by Li Jie, Wang Shuai, Lan Hai, Wang Zhiyong

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A Deep Reinforcement Learning-Driven Seagull Optimization Algorithm for Solving Multi-UAV Task Allocation Problem in Plateau Ecological Restoration by Lijing Qin, Zhao Zhou, Huan Liu, Zhengang Yan, Yongqiang Dai

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Attack resilient IoT security framework using multi head attention based representation learning with improved white shark optimization algorithm by Jawhara Aljabri

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DAG-based swarm learning: A secure asynchronous learning framework for Internet of Vehicles by Xiaoge Huang, Hongbo Yin, Qianbin Chen, Yu Zeng, Jianfeng Yao

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Collaborative altitude-adaptive reinforcement learning for active search with unmanned aerial vehicle swarms by XIAO Zijian, Chen-Chun Hsia, XU Yanggang, REN Jiyuan, CHEN Xinlei

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Optimizing data privacy and security measures for critical infrastructures via IoT based ADP2S technique by Zhenyu Xu, Jinming Wang, Shujuan Feng, Salwa Othmen, Chahira Lhioui, Aymen Flah, Zdenek Slanina

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Adaptive hybrid optimization for integrated project scheduling and staffing problem with time/resource trade-offs by Muhai Hu, Yao Wang, Wendi Tian

“…To solve this problem, we introduce an adaptive hybrid algorithm combining the Non-dominated Sorting Genetic Algorithm II (NSGA-II) and Multi-Objective Particle Swarm Optimization (MOPSO). …”
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A cluster based routing for maximizing the lifetime of underwater wireless sensor network using gravitational search algorithm by Shyamsundar R, Harshavarthan M, Shankar Thangavelu

“…The proposed GSA has been compared with competitive meta-heuristic algorithms, including Particle Swarm Optimization, Whale Optimization Algorithm, and Moth Flame Optimizer.…”
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Optimization Design of Lazy-Wave Dynamic Cable Configuration Based on Machine Learning by Xudong Zhao, Qingfen Ma, Jingru Li, Zhongye Wu, Hui Lu, Yang Xiong

“…A high-fidelity surrogate model based on a backpropagation (BP) neural network was trained to accurately predict cable dynamic responses. Three optimization algorithms—Particle Swarm Optimization (PSO), Ivy Optimization (IVY), and Tornado Optimization (TOC)—were evaluated for their effectiveness in optimizing the arrangement of buoyancy and weight blocks. …”
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An optimized public opinion communication system in social media networks based on K-means cluster analysis by Mingchao Qi, JunQiang Zhao, Yan Feng

“…This study proposes a public opinion monitoring model that combines the K-means clustering algorithm with Particle Swarm Optimization (PSO) to enhance the accuracy and effectiveness of public opinion monitoring on social media. …”
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Research on path planning for mine rescue UAV based on improved Artificial Jellyfish Search algorithm by ZHENG Xuezhao, DIAO Chengze, CAI Guobin, WEN Hu, YANG Bo, HOU Zongxuan, MOU Haowei

“…UAV path planning simulation experiments showed that, when the obstacle ratio was 14.56%, compared with the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, and JS algorithm, the IJS algorithm reduced the path planning time by 72.27%, 66.12%, and 70.87%, respectively; shortened the path length by 2.67%, 3.95%, and 1.36%, respectively; and reduced the number of turning points by 47.37%, 50%, and 28.57%, respectively. …”
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