Low-Resolution Quantized Precoding for Multiple-Input Multiple-Output Dual-Functional Radar–Communication Systems Used for Target Sensing by Xiang Feng, Zhongqing Zhao, Jiongshi Wang, Jian Wang, Zhanfeng Zhao, Zhiquan Zhou

“…To tackle this issue, we develop a weighted optimization framework that minimizes the mean squared error between the transmitted symbols and their estimates while satisfying specific radar performance requirements. …”
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Multi-Skilled Project Scheduling for High-End Equipment Development Considering Newcomer Cultivation and Duration Uncertainty by Yaohui Liu, Ronggui Ding, Shanshan Liu, Lei Wang

“…The model aims to minimize expected makespan and maximize newcomers’ skill efficiency by optimizing workforce assignment that enables experienced workers to mentor newcomers while simultaneously optimizing task scheduling. …”
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Quasi-preview control: A novel method for active structural vibration control subject to seismic disturbances using adaptive filters and multiple remote seismic observations by Shinya FUJIMURA, Tomohiro WATANABE, Kazuhiko HIRAMOTO

“…All design parameters in the quasi-preview control are optimized with the particle swarm optimization (PSO) algorithm. …”
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The development of an intelligent comprehensive detection instrument for circuit breakers in power systems and its key technologies by Weimin Guan, Han Hu, Chao Sun, Jie Ji

“…Additionally, this study optimizes the fault diagnosis algorithm, enhancing detection stability and robustness. …”
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A Semi-Trailer Path Planning Method Considering the Surrounding Traffic Conditions and Vehicle Roll Stability by Haochuan Zhang, Zhigen Nie, Yufeng Lian

“…Subsequently, we apply a particle swarm optimization algorithm to enhance the B-spline curve. …”
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An Adaptive Control Strategy for a Virtual Synchronous Generator Based on Exponential Inertia and Nonlinear Damping by Huiguang Pian, Keqilao Meng, Hua Li, Yongjiang Liu, Zhi Li, Ligang Jiang

“…Control parameters are optimized using an enhanced particle swarm optimization (PSO) algorithm based on a composite performance index that accounts for frequency deviation, overshoot, settling time, and power tracking error. …”
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Adaptive Temporal Reinforcement Learning for Mapping Complex Maritime Environmental State Spaces in Autonomous Ship Navigation by Ruolan Zhang, Xinyu Qin, Mingyang Pan, Shaoxi Li, Helong Shen

“…The model integrates an enhanced Proximal Policy Optimization (PPO) algorithm for efficient policy iteration optimization. …”
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Durability prediction of sustainable marine concrete under freeze-thaw cycles using multi-objective machine learning models by Aïssa Rezzoug, Ali H. AlAteah, Sadiq Alinsaif, Sahar A. Mostafa

“…This study introduces machine learning (ML)-based algorithms for forecasting FTC-induced durability of concrete while simultaneously predicting sustainability metrics such as CO₂ emissions and production cost. …”
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Sensorless real-time solar irradiance prediction in grid-connected PV systems using PSO-MPPT and IoT-enabled monitoring by Ali Zaki Mohammed Nafa, Adel A. Obed, Ahmed J. Abid, Salam J. Yaqoob, Mohit Bajaj, Mohammad Shabaz

“…The approach leverages the maximum power point current ( $$\:{\text{I}}_{\text{mpp}}$$ ) and voltage ( $$\:{\text{V}}_{\text{mpp}}$$ ) measured directly from a PV module to predict irradiance, utilizing a Particle Swarm Optimization (PSO)-based Maximum Power Point Tracking (MPPT) algorithm to ensure accurate tracking of power output across varying irradiance levels. …”
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Green Video Transcoding in Cloud Environments Using Kubernetes: A Framework With Dynamic Renewable Energy Allocation and Priority Scheduling by B. M. Beena, Prashanth Cheluvasai Ranga, A. Vinitha Chowdary, Rohan Gamidi, M. Hemasri, Tejaswi Muppala

“…The research addresses these challenges by developing a green, energy-aware video transcoding system that predicts energy availability from renewable sources (solar and wind) using machine learning techniques and optimizes tasks allocation. The system utilizes a Kubernetes-managed backend to dynamically scale resources for FFmpeg-based transcoding while prioritizing renewable energy, minimizing grid usage utilizing the advanced machine learning models, including Random Forest, XGBoost, and CatBoost, predict energy production and guide task assignments. …”
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Interacting Large Language Model Agents. Bayesian Social Learning Based Interpretable Models by Adit Jain, Vikram Krishnamurthy

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How many grid-forming converters are needed? – A techno-economic perspective by Guoxuan Cui, Hongyang Jia, Ning Zhang, Fei Teng

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Stability analysis of semi-submersible floating wind turbines based on gyro-turbine coupled dynamics model by Wancheng Wang, Hao Li, Yihang Yang, Kai Sheng, Lijing Chen

“…Based on this model, an innovative PSO-optimized fuzzy control strategy is proposed, utilizing intelligent particle swarm optimization algorithms to adjust controller parameters for optimal performance under various environmental conditions. …”
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Leveraging machine learning to proactively identify phishing campaigns before they strike by Kun Zhang, Haifeng Wang, Meiyi Chen, Xianglin Chen, Long Liu, Qiang Geng, Yu Zhou

“…To further refine classification accuracy across legitimate, suspicious, and phishing categories, hyperparameter tuning was performed using four nature-inspired optimization algorithms: Golden Jackal Optimization, Dandelion Optimization, Coati Optimization, and Puma Optimization. …”
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Prediction Model of Water Demand for Scouring Siltation in Coastal River Networks Based on APSO and SVM: A Case Study of Doulong Port by MA Zhutong, XIANG Long, YAN Ke

“…A predictive model of water demand for scouring siltation was constructed, which combined adaptive particle swarm optimization (APSO) algorithm with support vector machine (SVM) and optimized the model parameters of the SVM through the APSO algorithm, enhancing the prediction accuracy of the APSO-SVM model. …”
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Prediction Model of Water Demand for Scouring Siltation in Coastal River Networks Based on APSO and SVM: A Case Study of Doulong Port by MA Zhutong, XIANG Long, YAN Ke

“…A predictive model of water demand for scouring siltation was constructed, which combined adaptive particle swarm optimization (APSO) algorithm with support vector machine (SVM) and optimized the model parameters of the SVM through the APSO algorithm, enhancing the prediction accuracy of the APSO-SVM model. …”
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Evapotranspiration Prediction Method Based on K-Means Clustering and QPSO-MKELM Model by Chuansheng Zhang, Minglai Yang

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Dynamic UAV Task Allocation and Path Planning with Energy Management Using Adaptive PSO in Rolling Horizon Framework by Zhen Han, Weian Guo

“…We introduce an enhanced Particle Swarm Optimization (PSO) algorithm, incorporating adaptive perturbation strategies and a local search mechanism based on simulated annealing, to optimize UAV task assignments and routes. …”
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Machine Learning-Based Sentiment Analysis in English Literature: Using Deep Learning Models to Analyze Emotional and Thematic Content in Texts by Jie Yu, Chunhong Qi

“…Hyperparameter optimization is performed using the Improved Particle Swarm Optimization (IPSO) algorithm to fine-tune the model for efficient sentiment extraction. …”
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Fatigue-Aware Sub-Second Combinatorial Auctions for Dynamic Cycle Allocation in Human–Robot Collaborative Assembly by Claudio Urrea

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