6G virtualized beamforming: a novel framework for optimizing massive MIMO in 6G networks by Ahmed M. Alwakeel

“…Our framework employs a combination of advanced machine learning algorithms and software-defined networking to dynamically allocate beamforming resources, improving adaptability in high-density environments and optimizing signal-to-noise ratios. …”
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A deep neural network approach for optimizing charging behavior for electric vehicle ride-hailing fleet by Kaizhe Chen, Jin Liu, Wenjing Lyu, Tianyuan Wang, Jinxi Wen

“…Therefore, this research develops a Neural Network (NN) trained with the Adaptive Moment Estimation (Adam) algorithm, based on 2.14 million charging events. The goal is to analyze current charging behaviors and evaluate the impact of key variables on costs and emissions, providing data-driven insights for potential improvements, thus addressing a critical research gap. …”
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Investigation on Durability Behaviour and Optimization of Concrete with Triple-Admixtures Subjected to Freeze-Thaw Cycles in Salt Solution by Xuejiao Li, Wensheng Wang, Zhiqing Zhu, Kunkun Zheng

“…After that, based on genetic algorithm, an optimization of mixture proportion was proposed, which only requires less trial mixes and accessible optimization process. …”
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Developing a novel approach for passive damped LCL filter and controller parameter design using PSO algorithm in VSC-based islanded microgrids by Yared Bekele Beyene, Getachew Biru Worku, Lina Bertling Tjernberg

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LDC-GAT: A Lyapunov-Stable Graph Attention Network with Dynamic Filtering and Constraint-Aware Optimization by Liping Chen, Hongji Zhu, Shuguang Han

“…To address these issues, we propose LDC-GAT (Lyapunov-Stable Graph Attention Network with Dynamic Filtering and Constraint-Aware Optimization), which jointly optimizes both forward and backward propagation processes. …”
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Numerical Optimization of Laser Powder Bed Fusion Process Parameters for High-Precision Manufacturing of Pure Molybdenum by İnayet Burcu Toprak, Nafel Dogdu, Metin Uymaz Salamci

“…Optimization of process parameters is performed using FLOW-3D Release 7 software in conjunction with the HEEDS-SHERPA algorithm. …”
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Optimization and prediction of corporate credit rating through advanced feature selection based on AI and deep learning by Jumanah Ahmed Darwish

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Method and Optimization of Key Parameters of Soil Organic Matter Detection Based on Pyrolysis Coupled with Artificial Olfaction by Mingwei Li, Xiao Li, Xuexun Li, Wenjun Wang, Yulong Chen, Long Zhou, Xiaomeng Xia

“…Finally, the Back-Propagation Neural Network (BPNN) and Partial Least-Squares Regression (PLSR) algorithms were used to establish an SOM prediction model after obtaining soil pyrolysis gases under the optimal combination of pyrolysis parameters. …”
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A binary gridding path-planning method for plant-protecting UAVs on irregular fields by Wang-ying XU, Xiao-bing YU, Xin-yu XUE

“…In this study, we proposed a binarization multi-objective model for the irregular field area, specifically an improved non-dominated sorting genetic algorithm–II based on the knee point and plane measurement (KPPM-NSGA-ii). …”
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Explainable AI-Based Skin Cancer Detection Using CNN, Particle Swarm Optimization and Machine Learning by Syed Adil Hussain Shah, Syed Taimoor Hussain Shah, Roa’a Khaled, Andrea Buccoliero, Syed Baqir Hussain Shah, Angelo Di Terlizzi, Giacomo Di Benedetto, Marco Agostino Deriu

“…To address these limitations, this study proposes a comprehensive pipeline combining transfer learning, feature selection, and machine-learning algorithms to improve detection accuracy. Multiple pretrained CNN models were evaluated, with Xception emerging as the optimal choice for its balance of computational efficiency and performance. …”
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Optimizing blood glucose predictions in type 1 diabetes patients using a stacking ensemble approach by Vincent B. Liu, Laura Y. Sue, Oscar Madrid Padilla, Yingnian Wu

“…GRU had the best predictive accuracy of the initial models. Grey Wolf optimization contributed to achieving optimal baseline model results. …”
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Optimal path selection and secured data transmission in underwater acoustic sensor networks: LSTM-based energy prediction. by Sathish Kaveripakam, Ravikumar Chinthaginjala

“…Further, the data is transmitted via the optimal path securely by encrypting the data with the proposed improved blowfish algorithm (IBFA). …”
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Optimizing Stroke Risk Prediction: A Primary Dataset‐Driven Ensemble Classifier With Explainable Artificial Intelligence by Md. Maruf Hossain, Md. Mahfuz Ahmed, Md. Rakibul Hasan Rakib, Mohammad Osama Zia, Rakib Hasan, Md. Rakibul Islam, Md. Shohidul Islam, Md Shahariar Alam, Md. Khairul Islam

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Landslides in the Himalayas: The Role of Conditioning Factors and Their Resolution in Susceptibility Mapping by Lalit Pathak, Badri Baral, Kamana Joshi, Dipak Raj Basnet, Danilo Godone

“…Sixteen factors, encompassing topography, hydrology, geology, and anthropogenic activities, were analyzed alongside a landslide inventory of 159 occurrences compiled from satellite imagery, the literature, and field surveys. A genetic algorithm (GA) was employed to determine the optimal set of conditioning factors, while Maximum Entropy (Maxent) modeling produced landslide susceptibility maps (LSM) at spatial resolutions ranging between 12.5 and 200 m. …”
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Opportunities and challenges of quantum computing for climate modeling by Mierk Schwabe, Lorenzo Pastori, Inés de Vega, Pierre Gentine, Luigi Iapichino, Valtteri Lahtinen, Martin Leib, Jeanette Miriam Lorenz, Veronika Eyring

“…We discuss how quantum computers could accelerate climate models by solving the underlying differential equations faster, how quantum machine learning could better represent subgrid-scale phenomena in ESMs even with currently available noisy intermediate-scale quantum devices, how quantum algorithms aimed at solving optimization problems could assist in tuning the many parameters in ESMs, a currently time-consuming and challenging process, and how quantum computers could aid in the analysis of climate models. …”
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Optimizing Energy Efficiency in UPA-Assisted SWIPT Massive MIMO Systems Over Rician Fading Channels by Mohammad Hassan Adeli, Dariush Abbasi-Moghadam, Hossein Fotouhi, S. Mohammad Razavizadeh

“…Results demonstrate the superiority of our proposed design compared to the conventional scenarios with equal power allocation and fixed PS ratio algorithms with about 2 to 5 times EE improvements. …”
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Energy-Efficient Target Area Imaging for UAV-SAR-Based ISAC: Beamforming Design and Trajectory Optimization by Jiayi Zhou, Xiangyin Zhang, Kaiyu Qin, Feng Yang, Libo Wang, Deyu Song

“…Numerical results demonstrate that compared to existing benchmarks and PSO algorithms, the proposed method significantly improves the energy efficiency of UAV-SAR-based ISAC systems through optimized trajectory design.…”
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Optimization of PV parameters under varied environmental conditions: A hybrid secant–Newton-Raphson method by Brahim El Fahmi, Driss Saadaoui, Imade Choulli, Khalid Assalaou, Ismail Abazine, Mustapha Elyaqouti, El hanafi Arjdal, Mohammed Agdam, Yassine El aidi Idrissi

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Optimized Identification of Sentence-Level Multiclass Events on Urdu-Language-Text Using Machine Learning Techniques by Somia Ali, Uzma Jamil, Muhammad Younas, Bushra Zafar, Muhammad Kashif Hanif

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Architectural Exploration and Performance Enhancement of the CVA6 RISC-V Core Using the Gem5 Simulation Framework by Umer Shahid, Muhammad Tahir, Bilal Zafar, Ayesha Ahmad, Shanzay Wasim, Bisal Saeed

“…This approach resulted in two distinct optimized models: a resource-efficient variant that reduced resource consumption by 12% with only a 0.2% decrease in RMS micro-benchmark IPC, and a performance-optimized model that improved performance by 29.5% while increasing resource usage by just 4.20%. …”
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