Artificial Intelligence in Wind Turbine Fault Detection and Diagnosis: Advances and Perspectives by Nejad Alagha, Anis Salwa Mohd Khairuddin, Zineddine N. Haitaamar, Obada Al-Khatib, Jeevan Kanesan

“…The global shift toward renewable energy, particularly wind power, underscores the critical need for advanced fault diagnosis systems to optimize wind turbine reliability and efficiency. While traditional diagnostic methods remain foundational, their limitations in addressing the nonlinear dynamics and operational complexity of modern turbines have accelerated the adoption of Artificial Intelligence (AI)-driven approaches. …”
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Urban Resilience and Energy Demand in Tropical Climates: A Functional Zoning Approach for Emerging Cities by Javier Urquizo, Hugo Rivera-Torres

“…The system’s capacity to adjust and optimize power distribution would be strengthened provided the algorithms were given the freedom to react dynamically to changes or disruptions brought about by distributed generation sources.…”
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Artificial Intelligence and Smart Technologies in Safety Management: A Comprehensive Analysis Across Multiple Industries by Jiyoung Park, Dongheon Kang

“…AI-driven solutions, such as predictive analytics, machine learning algorithms, IoT sensor integration, and digital twin models, are shown to proactively identify and mitigate potential hazards, optimize energy consumption, and enhance operational efficiency. …”
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Prediction of shut-off head for centrifugal pumps based on grey theory and GA-BP neural network by Dehui Yu, Jinfeng Zhang, Shouqi Yuan, Wensheng Ma, Xiaobang Bai, Yan Chen, Chao Wang

“…This paper presents a predictive model based on extensive experimental data, employing a back propagation (BP) neural network optimized via grey theory and genetic algorithms (GAs). …”
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Clinical application and immune infiltration landscape of stemness‐related genes in heart failure by Wenting Yan, Yanling Li, Gang Wang, Yuan Huang, Ping Xie

“…Feature selection was performed using two machine learning algorithms. Nomogram models were then constructed to predict HF risk based on the selected key genes. …”
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Monitoring Canopy Height in the Hainan Tropical Rainforest Using Machine Learning and Multi-Modal Data Fusion by Qingping Ling, Yingtan Chen, Zhongke Feng, Huiqing Pei, Cai Wang, Zhaode Yin, Zixuan Qiu

“…The results showed that RH80 was the optimal choice for the prediction model regarding percentile selection, and the RF algorithm exhibited the optimal performance in terms of accuracy and stability, with R² values of 0.71 and 0.60 for the training and testing sets, respectively, and a relative root mean square error of 21.36%. …”
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Cooperative control method for multi-agent ground fracturing truck group based on offline reinforcement learning by RuYi Wang, HuiShen Jiao, YingCheng Tian, Yi Zhao, SiQi Wang, Ke Zhang, Bo Huang, QinRui Sun, DanDan Zhu

“…The core of this method is an improved algorithm based on the TD3, which is enhanced by the incorporation of the CQL algorithm to improve the stability of the collaborative control strategy. …”
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Reliability Analysis of Three-dimensional Soil Slopes Considering Spatial Variability of Soil Parameters by Wan Yukuai, Zhou Yuqi, Shao Linlan, Wang Yuke, Zhang Fei

“…The particle swarm optimization (PSO) algorithm is refined with enhanced termination criteria and integrated with the 3D Bishop method to search for the minimum factor of safety (F). …”
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Сombat wounds microflora in modern warfare by V. P. Kovalchuk, N. S. Fomina, V. M. Kondratiuk, О. О. Fomin, Y. V. Lazarenko, K. V. Gumenyuk

“…Analysis of the clonal characteristics and antibiotic resistance of the most prevalent wound pathogens among individuals injured in the Russian-Ukrainian war to support microbiota surveillance of combat wounds and optimize treatment strategies. Materials and Methods. …”
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An Active RIS-Aided DFRC System for Improved Multi-User Communications by Ravi Patel, Aayush Singh, Keshav Singh, Shahid Mumtaz, Chih-Peng Li, Sudip Biswas

“…We develop a optimization algorithm that leverages weighted minimum mean square error (WMMSE) and fractional programming techniques to maximize the weighted sum rate (WSR) for communication users while ensuring robust radar detection performance. …”
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Helicopter Turboshaft Engines’ Neural Network System for Monitoring Sensor Failures by Serhii Vladov, Łukasz Ścisło, Nina Szczepanik-Ścisło, Anatoliy Sachenko, Tomasz Perzyński, Viktor Vasylenko, Victoria Vysotska

“…The developed system demonstrated anomaly detection accuracy at 99.327% after 200 training epochs, with a reduction in loss from 2.5 to 0.5%, indicating stability in anomaly processing. A training algorithm incorporating temporal regularization and a combined optimization method (SGD with RMSProp) accelerated neural network convergence, reducing the training time to 4 min and 13 s while achieving an accuracy of 0.993. …”
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Transmitting Double-D Coil to Wirelessly Recharge the Battery of a Drone with a Receiving Coil Integrated in the Landing Gear by Wassim Boumerdassi, Tommaso Campi, Silvano Cruciani, Francesca Maradei, Mauro Feliziani

“…To this aim, a double-D configuration is here proposed and optimized for the transmitting coil, while a double coil receiver in combination with a charge controller that uses a maximum power point tracking (MPPT) algorithm is integrated into the landing gear. …”
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Quantitative structure-properties relationship, molecular dynamic simulations and designs of some novel lubricant additives by Usman Abdulfatai, Adamu Uzairu, Sani Uba, Gideon Adamu Shallangwa

“…Quantitative structure-properties relationship (QSPR) method was used to design some novel antioxidant lubricant additives, while molecular dynamics simulations were used to calculate their dynamic binding energies on steel and to hydrogen-containing DLC (a-C: H) crystal surfaces. 29 synthesized antioxidant lubricant additives were collected from literature and geometrically optimized by Spartan’14 version 1.1.2 software while Genetic Function Algorithm (GFA) method of the material studio version 8.0 software was used to build the predictive QSPR model. …”
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CFTformer: End-to-End Cross-Frame Multi-Object Tracking With Transformer by Abdollah Amirkhani, Seyed Alireza Khoshnevis

“…More accurate tracking and lower identity switches make this algorithm more suitable to be used in the field of autonomous driving. …”
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Drilling Condition Identification Method for Imbalanced Datasets by Yibing Yu, Huilin Yang, Fengjia Peng, Xi Wang

“…Secondly, a sliding-window-based Synthetic Minority Oversampling Technique (SMOTE) algorithm is developed, which generates new minority-class samples while preserving temporal dependencies, achieving balanced data distribution among classes. …”
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Designing a Sustainable Supply Chain Network for Perishable Products Integrating Internet of Things and Mixed Fleets by Lihong Pan, Xialian Li, Miyuan Shan

“…The model is solved using the Non-Dominated Sorting Genetic Algorithm II (NSGA-II). A case study based on real-world data demonstrates the model’s effectiveness. …”
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Stochastic Demand-Side Management for Residential Off-Grid PV Systems Considering Battery, Fuel Cell, and PEM Electrolyzer Degradation by Mohamed A. Hendy, Mohamed A. Nayel, Mohamed Abdelrahem

“…The optimization problem was solved using a genetic algorithm (GA), which efficiently explores the solution space to determine the optimal operating schedules and reduce degradation costs. …”
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YOLO-MES: An Effective Lightweight Underwater Garbage Detection Scheme for Marine Ecosystems by Chengxu Huang, Wenyuan Zhang, Beitian Zheng, Jiahao Li, Bochen Xie, Ruisi Nan, Zongming Tan, Baohua Tan, Neal N. Xiong

“…To address this issue, this paper introduces YOLO-MES, an innovative underwater debris detection algorithm that integrates a lightweight design and a feature enhancement mechanism to enable efficient model deployment while preserving high accuracy. …”
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Application of the Lagrange Equation for Intelligent Sensor Vibration Control for Power Network Monitoring by Xiaojing Cheng

“…The TMD natural frequency is 14.179 rad/s and the damping ratio is 0.0432 by the DH optimization method, while the TMD natural frequency is 14.1812 rad/s, and the damping ratio is 0.0436 by the augmented Lagrangian optimization algorithm. …”
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Earthquake Design of Reinforced Concrete Buildings Using NSGA-II by Herian A. Leyva, Edén Bojórquez, Juan Bojórquez, Alfredo Reyes-Salazar, José H. Castorena, Eduardo Fernández, Manuel A. Barraza

“…For this purpose, genetic algorithms (GAs) are used through the technique NSGA-II (Nondominated Sorting Genetic Algorithm), thus a multiobjective procedure with two objective functions is established. …”
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