Machine Learning and Deep Learning-Based Atmospheric Duct Interference Detection and Mitigation in TD-LTE Networks by Rasendram Muralitharan, Upul Jayasinghe, Roshan G. Ragel, Gyu Myoung Lee

“…Our results show that the Random Forest algorithm achieves the highest prediction accuracy, while a convolutional neural network demonstrates the best mitigation performance with accuracy. …”
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A Heterogeneous Image Registration Model for an Apple Orchard by Dongfu Huang, Liqun Liu

“…Then, we used the Sinkhorn AutoDiff algorithm to iteratively optimize and solve the optimal transmission problem, achieving optimal matching between feature points. …”
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MRSNet: Multi-Resolution Scale Feature Fusion-Based Universal Density Counting Network by Yi Zhang, Wei Song, Mingyue Shao, Xiangchun Liu

“…Lower-resolution features are more sensitive to larger objects closer to the camera, while higher-resolution features are more efficient for smaller objects further away. …”
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Improved Block Element Method for Simulating Rock Failure by Yan Han, Qingwen Ren, Lei Shen, Yajuan Yin

“…As the innovation of this work, the iterative algorithm is combined with polygonal geometric features so that the area–perimeter fractal dimension can be introduced to optimize random Voronoi grids. …”
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Analysis and Prediction of Thermally Induced Positioning Error in Hydrostatic Lead-Screw Feed Systems by Jun Zha, Xiaofei Peng, Zhiyan Cai, Fei Xue

“…To address this gap, this research proposes a novel method that integrates simulation with a data-driven optimization strategy. The core of our approach involves using the K-means clustering algorithm to optimize the selection of temperature measurement points on the hydrostatic screw nut, ensuring a more representative thermal characterization. …”
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An Adaptive Wireless Droop Control with Adaptive Virtual Resistance for Power Sharing Management in MTDC Grid by Hasan Alrajhi , Ahmed Al-Zahrani , Syed A. Raza , Fahad Al-Shareef 

“…Additionally, this communication-free scheme includes a power management algorithm that controls power sharing during peak hours of the inverters among the rectifiers as per mutual agreements between the operators to mitigate the risk of a system overload and optimize the power sharing. …”
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A Reinforcement Learning-based Intelligent Learning Method for Anti-active Jamming in Frequency Agility Radar by J. Wei, L. Yu, Y. Wei, R. Xu

“…This model includes five submodules: signal processing, anti-jamming evaluation, target detection, optimization constraint design, and optimization algorithm design. …”
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Data-driven framework for prediction of mechanical properties of waste glass aggregates concrete by Kennedy C. Onyelowe, Shadi Hanandeh, Viroon Kamchoom, Ahmed M. Ebid, Hamza Imran, Miguel Angel Duque Vaca, Greys Carolina Herrera Morales, Nestor Ulloa, Krishna Prakash Arunachalam

“…Abstract This research presents a novel data-driven framework for predicting the mechanical properties of waste glass aggregate concrete using six advanced metaheuristic optimization algorithms: Bat Algorithm (Bat), Cuckoo Search Algorithm (Cuckoo), Elephant Herding Optimization (Elephant), Firefly Algorithm (Firefly), Rhinoceros Optimization Algorithm (Rhino), and Gray Wolf Optimizer (Wolf). …”
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Enhancing proximal and remote sensing of soil organic carbon: A local modelling approach guided by spectral and spatial similarities by Qi Sun, Pu Shi

“…Different spectral similarity metrics, and weighted combinations of spectral and geographical similarity matrices were tested to optimize the selection of local training samples. As a result, the optimal modelling strategy, with partial least squares regression (PLSR) as the local fitting algorithm, consistently produced superior performances (R2: 0.66 to 0.82) than the conventional global modelling approach (R2: 0.59 to 0.77) for all three data types. …”
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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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New Approaches to AI Methods for Screening Cardiomegaly on Chest Radiographs by Patrycja S. Matusik, Zbisław Tabor, Iwona Kucybała, Jarosław D. Jarczewski, Tadeusz J. Popiela

“…The CTR and TCD were then calculated using these labels and a mathematical algorithm. For the training set, we retrospectively included 65 randomly selected patients who underwent CXRs, while for the testing set, we chose 50 patients who underwent cardiac magnetic resonance (CMR) imaging and had available CXRs in the medical documentation. …”
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Intelligent Office Lighting Control Using Natural Light and a GA-BP Neural Network-Based System by Rongmeng Zhang, Ruiqi Li, Junbai Lu, Haiqian E, Haotian Wang, Xinyu Zhao, Yingming Gao, Zhisheng Wang

“…This study addresses the issue of natural glare by proposing a method that uses a genetic algorithm (GA) to optimize a backpropagation (BP) neural network model. …”
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RSWD-YOLO: A Walnut Detection Method Based on UAV Remote Sensing Images by Yansong Wang, Xuanxi Yang, Haoyu Wang, Huihua Wang, Zaiqing Chen, Lijun Yun

“…Through model deployment and testing on small edge devices, we demonstrate the feasibility of our proposed method. The detection algorithm achieves 86.1% mean Average Precision on the walnut dataset while maintaining operational functionality on small edge devices. …”
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Intelligent deep learning for human activity recognition in individuals with disabilities using sensor based IoT and edge cloud continuum by Mohammed Maray

“…For feature subset selection, the enhanced honey badger algorithm (EHBA) model is used to effectively reduce dimensionality while retaining critical activity-related features. …”
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Ship-DETR: A Transformer-Based Model for EfficientShip Detection in Complex Maritime Environments by Yi Wang, Xiang Li

“…To address these issues, we propose an effective ship detection algorithm—Ship Detection Transformer (Ship-DETR). …”
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Development and Practice of Cloud Collaborative Platform for Downhole Measurement Tools by Che Yang, Yuan Guangjie, Qian Hongyu, Du Weiqiang, Wang Chenlong, Ding Jiping

“…In the paper， based on the remote operation requirements of coreless magnetic steering tool， a platform architecture of five modules， including simulation rehearsal， virtual training， remote operation， smart tool and intelligent decision， was designed in detail， achieving a whole process digitization from predrilling risk assessment and in-drilling acquisition and processing to post-drilling feedback and optimization， and a visual interface was developed. …”
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INCREASED COMPETITIVENESS OF CONSTRUCTION ENTERPRISES ON THE BASIS OF ORGANISATIONAL-ECONOMIC DECISIONS OF PERSONNEL POTENTIAL MANAGEMENT by J. R. Emirbekova

“…The development of an algorithm for optimising the formation and use of human resources of a construction enterprise.Methods. …”
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Modeling the Stability of the Housing and Construction Complex Based on Organizational and Economic Interaction of Entities by N. N. Shelomentseva, O. V. Grushina

“…A genetic algorithm in MATLAB was used for this purpose. Acceptable options for all participants were selected from a set of Pareto-optimal alternatives based on the preferences of the decision-maker. …”
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Enhanced Vector Quantization for Embedded Machine Learning: A Post-Training Approach With Incremental Clustering by Thommas K. S. Flores, Morsinaldo Medeiros, Marianne Silva, Daniel G. Costa, Ivanovitch Silva

“…While VQ is a technique that reduces model size by grouping similar parameters, incremental clustering, implemented via the AutoCloud K-Fixed algorithm, preserves accuracy during compression. …”
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DQN-Based Shaped Reward Function Mold for UAV Emergency Communication by Chenhao Ye, Wei Zhu, Shiluo Guo, Jinyin Bai

“…The experimental outcomes underscore the prowess of our methodology in effectively curtailing training time while augmenting convergence rates. In summary, our work underscores the potential of leveraging sophisticated virtual environments and refined reinforcement learning techniques to optimize UAVs deployment in emergency communication contexts.…”
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