Wind Turbine Stall‐Induced Aeroelastic Instability Mitigation Using Vortex Generators by Qingshen Meng, Chao Chen, Xugang Hua, Wei Yu

“…ABSTRACT Inspired by Vortex Generators' success in delaying airfoil stall, this study explores the potential of using Vortex Generators to mitigate stall‐induced instability in floating offshore wind turbines at parked and skewed inflow conditions for the first time. Significant improvements are achieved by strategically installing Vortex Generators in the outboard sections of turbine blades and optimizing their parameters (normalized height, length, inflow angle, and chordwise positions) using the particle swarm optimization algorithm and fast optimization method. …”
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Robust dispatch for electrical–thermal combined smart building considering impacts of uncertainties on thermal side by Weijie He, Fanrong Wei, Xiangning Lin, Samir M. Dawoud

“…The robust scheduling model proposed in this paper that considers the uncertainty on both sides jointly improves the conservatism of traditional scheduling schemes while achieving better economic benefits.…”
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A Deformation Prediction Model for Concrete Dams Based on RSA-VMD-AttLSTM by Pei Liu, Hao Gu, Chongshi Gu, Yanbo Wang

“…Analysis of the five evaluation criteria revealed that the RSA can better optimize the parameters of the VMD algorithm. Consequently, the proposed model demonstrates superior noise reduction capabilities and improved prediction accuracy.…”
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Analysis of the impact of mobile robots on the efficiency of warehousing and transport processes in modern textile manufacturing by Karabegović Isak

“…Studies indicate that the deployment of AMR technology can improve warehouse efficiency by up to 40% and reduce operational costs by as much as 25%, while also decreasing human error and enhancing workplace safety. …”
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Machine learning prediction of permeability distribution in the X field Malay Basin using elastic properties by Zaky Ahmad Riyadi, John Oluwadamilola Olutoki, Maman Hermana, Abdul Halim Abdul Latif, Ida Bagus Suananda Yogi, Said Jadid A. Kadir

“…Several ensemble-based models, including Extreme Gradient Boosting (XGBoost), Light Gradient Boosting (LightBoost), Categorical Gradient Boosting (CatBoost), Bagging Regressor, Random Forest and Stacking, were evaluated for predictive performance, along with Multi-Layered Perceptron Neural Network algorithms. Additionally, Tree-structured Parzen Estimator-Bayesian optimization method was utilized to optimize the machine learning model's hyperparameters and improve accuracy. …”
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Data stream mining techniques for real-time monitoring and control of smart power grids in Kenya: challenges and opportunities by Cornelius Mutuku Mulevu, George Onyango Okeyo, Joseph Muliaro Wafula

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A Low-Energy Lighting Strategy for High-Yield Strawberry Cultivation Under Controlled Environments by Jun Zou, Zihan Wang, Haitong Huang, Xiaohua Huang, Mingming Shi

“…The lighting system, which combines red (655–665 nm) and full-spectrum white LEDs, was optimized using a particle swarm optimization (PSO) algorithm to enhance spatial light distribution. …”
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Analysis of Techno–Economic and Social Impacts of Electric Vehicle Charging Ecosystem in the Distribution Network Integrated with Solar DG and DSTATCOM by Ramesh Bonela, Sriparna Roy Ghatak, Sarat Chandra Swain, Fernando Lopes, Sharmistha Nandi, Surajit Sannigrahi, Parimal Acharjee

“…In this work, a comprehensive planning framework for an electric vehicle charging ecosystem (EVCE) is developed, incorporating solar distributed generation (DG) and a distribution static compensator (DSTATCOM), to assess their long-term techno–economic and environmental impacts. The optimal locations and capacities of the EVCE, solar DG, and DSTATCOM are determined using an improved particle swarm optimization algorithm based on the success rate technique. …”
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Neural Architecture Search for Generative Adversarial Networks: A Comprehensive Review and Critical Analysis by Abrar Alotaibi, Moataz Ahmed

“…The review highlights the benefits of NAS in improving GAN performance, stability, and efficiency, while also identifying limitations and areas for future research. …”
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Bridging ACO-Based Drone Logistics and Computing Continuum for Enhanced Smart City Applications by Salvatore Rosario Bassolillo, Egidio D’Amato, Immacolata Notaro, Luca D’Agati, Giovanni Merlino, Giuseppe Tricomi

“…The proposed system addresses the Capacitated Vehicle Routing Problem (CVRP) by considering both drone capacity constraints and autonomy, using the ACO-based algorithm to efficiently assign delivery destinations while minimizing travel distances. …”
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Route Generation and Built Environment Behavioral Mechanisms of Generation Z Tourists: A Case Study of Macau by Ying Zhao, Pohsun Wang, Yafeng Lai

“…Building on this behavioral mechanism, an interest-based Ant Colony Optimization (ACO) algorithm is implemented by incorporating point-of-interest (POI) preferences and distance matrices to improve personalized route generation. …”
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Modeling 5G-NR User Blocking Probability in Conditional Handover-Enabled Heterogeneous Networks by Amiraslan Haghrah, Javad Musevi Niya, Jafar Pourrostam

“…To demonstrate the practical applicability of the proposed model, we present a case study involving a multi-objective optimization problem solved using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). …”
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Rotation reshapes sustainable potato production in dryland by reducing environmental footprints synergistically enhancing soil health by Hanyou Xie, Weiyan Wang, Ping He, Wencheng Ding, Xinpeng Xu, Xuelian Tan, Xiaowei Liu

“…Furthermore, the non-dominated sorting genetic algorithm II (NSGA-II) was used to optimize regional cropping structure. …”
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Adaptive control for vehicle formation movement with multiple sensors by TANG Mingzhu, XIANG Guoliang, SHI Hongwei, GUO Shenghui

“…The adaptive motion algorithm based on predetermined motion trajectories is studied in this paper, addressing the problem of vehicle formation with multiple sensors. …”
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Predicting Earthquake Casualties and Emergency Supplies Needs Based on PCA-BO-SVM by Fuyu Wang, Huiying Xu, Huifen Ye, Yan Li, Yibo Wang

“…Subsequently, the optimal hyperparameters for the SVM model are obtained using the Bayesian Optimization algorithm. …”
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Crash severity prediction using a virtual geometry-group-based deep learning approach with images-based feature representation by Nanon Sonnatthanon, Kasem Choocharukul

“…To address class imbalance, a combination of the Synthetic Minority over Sampling technique, Edited Nearest Neighbor, and Tomek Link algorithms are applied. A Virtual Geometry Group deep learning model, optimized using Bayesian optimization, is trained to maximize the F1-score and Area Under the Curve, ensuring high prediction performance. …”
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A novel hybrid extreme learning machine-based diagnosis model for sensor node faults in aquaculture by Bing Shi, Zelin Gao, Tianheng Pu, Jianming Jiang, Yueping Sun

“…Additionally, parameters such as $$\sigma ,\textrm{n} ,d,\gamma$$ in the hybrid kernel function, and the penalty coefficient C, were also optimized to improve classification accuracy. A diagnosis model of a hybrid extreme learning machine based on an updated particle swarm optimization for sensor node faults was developed. …”
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AI-Driven Predictive Maintenance in Mining: A Systematic Literature Review on Fault Detection, Digital Twins, and Intelligent Asset Management by Luis Rojas, Álvaro Peña, José Garcia

“…The findings highlight the increasing adoption of deep learning, reinforcement learning, and digital twins for anomaly detection and process optimization. Additionally, AI-driven methods are improving sensor-based data acquisition and asset management, extending equipment lifecycles while reducing failures. …”
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Adaptive drive-based integration technique for predicting rheological and mechanical properties of fresh gangue backfill slurry by Chaowei Dong, Jianfei Xu, Nan Zhou, Jixiong Zhang, Hao Yan, Zejun Li, Yuzhe Zhang

“…This is mainly because fine-grained (0–0.15 mm) GS improves the uniformity and density between particles in the slurry, while excess water content disrupts the balance provided by fine-grained GS, and the uneven distribution of particles in the slurry can be caused. …”
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Minimizing Delay in UAV-Aided Federated Learning for IoT Applications With Straggling Devices by Mudassar Liaq, Waleed Ejaz

“…We then use the concurrent deterministic simplex with root relaxation algorithm. We also propose a deep reinforcement learning (DRL)-based solution to improve runtime complexity. …”
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