Power Line Segmentation Algorithm Based on Lightweight Network and Residue-like Cross-Layer Feature Fusion by Wenqiang Zhu, Huarong Ding, Gujing Han, Wei Wang, Minlong Li, Liang Qin

“…Experimental results demonstrate that compared with classical UNet, the optimized network achieves 2.05% and 2.58% improvements in F1-Score and IoU, respectively, while reducing the parameter count to 57.25% of the original model. …”
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Fluid–Structure Interaction Study in Unconventional Energy Horizontal Wells Driven by Recursive Algorithm and MPS Method by Xikun Gao, Dajun Zhao, Yi Zhang, Yong Chen, Zhanzhao Gao, Xiaojiao Zhang, Shengda Wang

“…Key findings show that drilling fluid significantly impacts drill string behavior; for instance, it can reduce natural frequencies by 20–25%, while stiff formations amplify lateral resonance risks. …”
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Drought Amplifies the Suppressive Effect of Afforestation on Net Primary Productivity in Semi-Arid Ecosystems: A Case Study of the Yellow River Basin by Futao Wang, Ziqi Zhang, Mingxuan Du, Jianzhong Lu, Xiaoling Chen

“…Integrating multi-source remote sensing data (2000–2020), meteorological observations with the Standardized Precipitation Evapotranspiration Index (SPEI) and an improved CASA model, this study systematically investigates spatiotemporal patterns of vegetation net primary productivity (NPP) responses to extreme drought events while quantifying vegetation coverage’s regulatory effects on ecosystem drought sensitivity. …”
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Singular Value Decomposition (SVD) Method for LiDAR and Camera Sensor Fusion and Pattern Matching Algorithm by Kaiqiao Tian, Meiqi Song, Ka C. Cheok, Micho Radovnikovich, Kazuyuki Kobayashi, Changqing Cai

“…Unlike traditional calibration methods that require manual targets, our approach is targetless, extracting matched patterns from projected LiDAR point clouds and 2D image segments. The algorithm computes the optimal transformation matrix between sensors, correcting misalignments in rotation, translation, and scale. …”
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Algorithm for Managing Patients Hospitalized in the Surgical Wards Due to COVID-19-Related Acute Abdominal Pathology by D. G. Buribayev, D. B. Tulyaganov, Kh. E. Anvarov

“…The application of the developed algorithm will optimize the management of patients with COVID-19-related acute surgical pathology, guarantee rapid decision-making while minimizing the risk of infection, reduce the risk of complications and adverse outcomes.…”
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Synergetic simplified super-twisting algorithm control for stability enhancement of PV/BESS-based DC microgrid by Naamane Debdouche, Ali Chebabhi, Habib Benbouhenni, Fatma-Zohra Hadjaidji, Z. M. S. Elbarbary, Saad F. Al-Gahtani

“…It ensures the desired voltage level at the common DC bus while tailoring energy allocation to meet load requirements. …”
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Emerging technologies in airway management: a narrative review of intubation robotics and anatomical structure recognition algorithms by Weixiong Chen, Yu Tian, Yingjie Wang, Lili Feng, Mannan Abdul, Shuangshuang Li, Wenxian Li, Yuan Han

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Optimizing the lifetime of wireless sensor networks via reinforcement-learning-based routing by Wenjing Guo, Cairong Yan, Ting Lu

“…Reinforcement-learning-based routing protocol takes advantage of the intelligent algorithm of reinforcement learning to search for the optimal routing path for data transmission. …”
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Improved energy efficiency using meta-heuristic approach for energy harvesting enabled IoT network by Rekha, Ritu Garg

“…OPA-APSO differs from most existing approaches as it considers the amount of energy harvested while optimizing the solution. Finally, simulation results demonstrate that OPA-APSO improves energy efficiency and throughput of the network significantly as compared to other existing techniques. …”
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Operational response to contamination in water distribution systems: a multi-objective Bayesian optimization approach by Khalid Alnajim, Ahmed A. Abokifa

“…The optimization framework aims to balance the conflicting objectives of minimizing response time while maximizing water quality metrics after contamination events. …”
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Gait and Trajectory Optimization by Self-Learning for Quadrupedal Robots with an Active Back Joint by Ariel Masuri, Oded Medina, Shlomi Hacohen, Nir Shvalb

“…The algorithm actively optimizes 12 of the robot’s dynamic walking parameters. …”
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A Spatial–Temporal Time Series Decomposition for Improving Independent Channel Forecasting by Yue Yu, Pavel Loskot, Wenbin Zhang, Qi Zhang, Yu Gao

“…The main advantage of the proposed forecasting framework for multivariate time series is that it retains the interpretability and simplicity of single-channel forecasting methods while improving their accuracy by capturing information about the spatial-channel dependencies. …”
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Modeling and Optimization of Beam Pumping System Based on Intelligent Computing for Energy Saving by Xiaohua Gu, Taifu Li, Zhiqiang Liao, Liping Yang, Ling Nie

“…It firstly employs the general regression neural network (GRNN) algorithm to obtain the best model of the beam pumping system, and secondly searches the optimal operation parameters with improved strength Pareto evolutionary algorithm (SPEA2). …”
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Improving parking availability prediction in smart cities with IoT and ensemble-based model by Stéphane Cédric Koumetio Tekouabou, El Arbi Abdellaoui Alaoui, Walid Cherif, Hassan Silkan

“…The tests that we carried out on the Birmingham parking data set allowed to reach a Mean Absolute Error (MAE) of 0.06% on average with the algorithm of Bagging Regression (BR). This results have thus improved the best existing performance by over 6.6% while dramatically reducing system complexity.…”
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Research on Adaptive Planning of Three-Dimensional Trajectory for Uncrewed Aerial Vehicle Inspection Based on Nonlinear Weibull Algorithm by Zhuang Liu, Ning Yang, Jiaxing Fu, Huanqing Cai, Xuebei Wei

“…An S-shaped characteristic function-based nonlinear evolution factor is employed to balance global exploration and local exploitation of the optimal path, while a Weibull flight operator mutation strategy is designed to enable the algorithm to escape from locally optimal paths, enrich the search space, and improve convergence accuracy. …”
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Machine Learning-Driven Prediction of Vitamin D Deficiency Severity with Hybrid Optimization by Usharani Bhimavarapu, Gopi Battineni, Nalini Chintalapudi

“…The improved whale optimization (IWOA) algorithm was used for feature selection, which optimized weight functions to improve prediction accuracy. …”
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Optimization of signal control at ramp adjacent intersections based on A2C by SONG Tailong, GUO Mingyang, CHEN Yifan, HE Yulong

“…This study utilizes deep reinforcement learning algorithms for traffic signal control optimization at exit ramps associated with intersection crossings. …”
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Improved stereo matching network based on dense multi-scale feature guided cost aggregation by ZHANG Bo, ZHANG Meiling, LI Xue, ZHU Lei

“…To further improve the disparity prediction accuracy of stereo matching algorithm in the ill-posed regions such as repeating textures, no texture, and edge, an improved dense multi-scale feature guided aggregation network (DGNet) based on PSMNet was proposed. …”
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Research on coal mine robot positioning algorithm based on integration of ORB-SLAM3 vision and inertial navigation by Wei CHEN, Shuaida WU, Zijian TIAN, Fan ZHANG, Yi LIU

“…According to the principle of tight coupling of visual inertial navigation, the residual function of the whole positioning system is constructed by fusing visual residual error and IMU residual error, and the sliding window BA algorithm based on nonlinear optimization is used to iteratively optimize the residual function to obtain accurate pose estimation of the mobile robot. …”
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Hybrid Optimization Machine Learning Framework for Enhancing Trust and Security in Cloud Network by Himani Saini, Gopal Singh, Amrinder Kaur, Sunil Saini, Niyaz Ahmad Wani, Vikram Chopra, Zahid Akhtar, Shahid Ahmad Bhat

“…For resource allocation, the framework employs the Time-aware modified best fit decreasing (T-MBFD) algorithm, which adapts to fluctuating workloads. Key input parameters for T-MBFD include available resources, job size, and time constraints, while output parameters focus on optimized resource distribution and minimizing wastage. …”
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