AI-driven generative and reinforcement learning for mechanical optimization of 2D patterned hollow structures by Yicheng Shan, Leitao Cao, Yu Wang, Jing Ren, Chen Huang, Wenli Gao, Shengjie Ling

“…In this study, we develop an integrated framework combining conditional generative adversarial networks (cGANs) and deep Q-networks (DQNs) to predict and optimize the stress fields of 2D-PHS. …”
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AoI-enabled multi-node cooperative sensing based on integration of sensing, communication, and computing in vehicular networks by Yiqing ZHOU, Haoyue ZHANG, Yanli QI, Qing CAI, Ling LIU, Jiangzhou WANG

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Hybrid design of optimal shunt capacitor allocation and reconfiguration of radial distribution systems considering techno-economic benefits by Ifeoluwa Olajide Fajinmi, Gafari Abiola Adepoju, Sunday Adeleke Salimon, Kareem M. AboRas, Oluwaseyi Wasiu Adebiyi, Olubunmi Onatoyinbo, Mohammad Khishe, Pradeep Jangir, Wulfran Fendzi Mbasso

“…Hence, this study provides an innovative method for the performance enhancement of radial distribution networks (RDNs) through simultaneous reconfiguration and Shunt Capacitor (SC) allotment utilizing a newly developed Dandelion Optimizer (DO) and a novel objective function. …”
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Performance Evaluation of a Radial Distribution Network Under Emerging Load Prediction Modeling Approach and DG Integration Using a Particle Swarm Optimization Algorithm by Demsew Mitiku Teferra

“…This research presents a comprehensive performance evaluation of an 11-bus, 15 kV radial distribution network in Ethiopia, utilizing particle swarm optimization (PSO) to assess the impact of emerging load prediction models and distributed generation (DG) integration. …”
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Comparing Strategies for Optimal Pumps as Turbines Selection in Pressurised Irrigation Networks Using Particle Swarm Optimisation: Application in Canal del Zújar Irrigation Distric... by Mariana Akemi Ikegawa Bernabé, Miguel Crespo Chacón, Juan Antonio Rodríguez Díaz, Pilar Montesinos, Jorge García Morillo

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Improved Snake Optimization Algorithm for Global Optimization and Engineering Applications by Kaiyuan Zheng, Huiyong Liu, Bopeng Li

“…Results showed ISO’s superior performance in convergence speed, stability, and global optimization. Furthermore, ISO was successfully applied in four engineering domains: UAV path planning, robot path planning, wireless sensor network node deployment, and pressure vessel design. …”
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Minimizing System Entropy: A Dual-Phase Optimization Approach for EV Charging Scheduling by Wenpeng Yuan, Lin Guan

“…To address the electric vehicle (EV) charging scheduling problem in rural distribution networks, this study proposes a novel two-phase optimization strategy that combines particle swarm optimization (PSO) and Q-learning for global optimization and real-time adaptation. …”
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Dynamic climate graph network and adaptive climate action strategy for climate risk assessment and low-carbon policy responses by Fang Zhou, Yan Shi, Pengfei Zhao, Zhengzhao Gu, Ye Li

“…ACAS builds upon DCGN’s predictive outputs by applying attention mechanisms and optimization under domain-specific constraints to prioritize high-impact regions and variables.ResultsEmpirical results demonstrate that the proposed framework consistently outperforms several state-of-the-art baselines across multiple benchmark datasets, achieving an average improvement of over 2.5% in F1 Score and AUC. …”
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Research on the Time Series Prediction of Acoustic Emission Parameters Based on the Factor Analysis–Particle Swarm Optimization Back Propagation Model by Xuebin Xie, Meng Wang

“…Additionally, it is found that the BP neural network optimized by Particle Swarm Optimization (PSO) is more suitable for predicting the future evolution of these AE parameters. …”
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Hybrid AI and Big Data Solutions for Dynamic Urban Planning and Smart City Optimization by Wei Zhu, Wei He, Qingsong Li

“…This study introduces a novel approach by combining Graph Neural Networks (GNNs) with Simulated Annealing (SA) to tackle these challenges in urban planning. …”
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SC-Route: A Scalable Cross-Layer Secure Routing Method for Multi-Hop Inter-Domain Wireless Networks by Yanbing Li, Yang Zhu, Shangpeng Wang

“…To address these limitations, we propose a new routing method—the Secure Cross-Layer Route—designed for multi-hop inter-domain wireless networks to achieve unified optimization of security, delay, and throughput. …”
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Establishment of an Improved Elman Neural Network Model for Predicting the Corrosion Rate of 3C Steel in Marine Environment and Analysis of the Factors Affecting Model Accuracy by Wenbo Jin, Zhuo Chen, Wanying Liu, Qing Quan, Zongxiao Ren

“…Based on the experimental data of corrosion rates of 3C steel in different seawater environments, an improved Elman neural network model was established by using the whale optimization algorithm. …”
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SPARCQ: Enhancing Scalability and Adaptability of Proactive Edge Caching Through Q-Learning by Shruti Lall, Johan de Clercq, Nelishia Pillay, Bodhaswar T. Maharaj

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RL-SCAP SigFox: A Reinforcement Learning Based Scalable Communication Protocol for Low-Power Wide-Area IoT Networks by Raghad Albalawi, Fatma Bouabdallah, Linda Mohaisen, Shireen Saifuddin

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Power control strategy with joint of multi-packet reception and fuzzy logic control by Jiang-hong HAN, Song-hua HU, Bin LIU, Zhen CHEN, Lei LIU

“…In order to meet the needs of energy saving in wireless networks,a power control strategy with joint of multi-packet reception and fuzzy logic was proposed.Firstly,based on the power control with successive interference cancellation (SIC),transmission power was divided into several decodable power levels.Secondly,fuzzy logic control algorithm was adopted to select the optimal transmission power for SIC.In addition,three parameters were designed as fuzzy logic control inputs for power selection,which were the distance between transmitters and receivers,the number of neighboring nodes and the residual energy of transmitters.Simulation results show that power control strategy with joint of multi-packet reception and fuzzy logic control not only betters average network throughput than other power control strategy for SIC,but also saves more energy so that the network lifecycle would be significantly extended.…”
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Power control strategy with joint of multi-packet reception and fuzzy logic control by Jiang-hong HAN, Song-hua HU, Bin LIU, Zhen CHEN, Lei LIU

“…In order to meet the needs of energy saving in wireless networks,a power control strategy with joint of multi-packet reception and fuzzy logic was proposed.Firstly,based on the power control with successive interference cancellation (SIC),transmission power was divided into several decodable power levels.Secondly,fuzzy logic control algorithm was adopted to select the optimal transmission power for SIC.In addition,three parameters were designed as fuzzy logic control inputs for power selection,which were the distance between transmitters and receivers,the number of neighboring nodes and the residual energy of transmitters.Simulation results show that power control strategy with joint of multi-packet reception and fuzzy logic control not only betters average network throughput than other power control strategy for SIC,but also saves more energy so that the network lifecycle would be significantly extended.…”
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Facility location problem for senior centers in an upcoming super-aging society by Eun Hak Lee, Jonghwa Jeong

“…This study aims to address the facility location problem for senior centers in upcoming super-aging societies. An optimization model is developed using a genetic algorithm to determine the optimal locations of senior centers. …”
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OPTICALS: A Novel Framework for Optimizing Predictive Trading Indicators in Cryptocurrency Using Advanced Learning Simulations by Hasib Shamshad, Fasee Ullah, Syed Adeel Ali Shah, Muhammad Faheem, Beena Shamshad

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Inverse Gini indexed averaging: A multi-leveled ensemble approach for skin lesion classification using attention-integrated customized ResNet variants by Anwar Hossain Efat, SM Mahedy Hasan, Md Palash Uddin, Faysal Hossain Emon

“…We propose an innovative weight optimization method, inverse Gini indexed averaging (IGIA), which is further extended to multi-leveled IGIA (ML-IGIA) to determine the optimal weights for each model within multiple ensemble levels. …”
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Artificial Neural Network and Response Surface Methodology-Driven Optimization of Cu–Al₂O₃/Water Hybrid Nanofluid Flow in a Wavy Enclosure with Inclined Perio... by Tarikul Islam, Sílvio Gama, Marco Martins Afonso

“…At the same time, artificial neural networks (ANNs) and response surface methodology (RSM) are employed to optimize thermal performance by maximizing the average Nusselt number (<i>Nu</i>_av), the key indicator of thermal transport efficiency. …”
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