Automatic mosaic method of remote sensing images based on machine vision by S.P. Gao, M. Xia, S.J. Zhang

“…To address the above issues, this study proposes an improved remote sensing image mosaic model on the bias of the Scale Invariant Feature Transform (SIFT) algorithm. …”
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Risk identification and assessment of Internet public opinion on public emergencies based on Bayesian network and association rule mining by Mengjie You, Xuwei Pan, Chuwen Zhu

“…The core innovation lies in designing an improved scheme based on the CBA (Classification Based on Associations) algorithm to overcome the limitation of traditional association rule mining in handling non-Boolean data, thereby effectively extracting the correlations among public opinion risk factors to optimize the topological structure of the BN. …”
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Air-ground collaborative multi-source orbital integrated detection system: Combining 3D imaging and intrusion recognition. by Mengyuan Yan, Xingyu Yang, Wei Gao, Lifan Rong, Shengbo Li, Yuan Xiong

“…The system employs a lightweight rail inspection vehicle equipped with dual LiDARs and an Astro camera, synchronized with an unmanned aerial vehicle (UAV) carrying industrial-grade LiDAR. We propose an improved LiDAR odometry and mapping with sliding window (LOAM-SLAM) algorithm enables real-time dynamic mapping, while an optimized iterative closest point (ICP) algorithm achieves high-precision point cloud registration and colorization. …”
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A 3D acid fracturing design calibrated to describe the productivity index in several southwestern Iranian oil fields by Mohammad Mirhashemi, Kaveh Ahangari, Ali Naghi Dehghan, Kamran Goshtasbi

“…By assessing these input parameters, the study aims to optimize the conditions under which acid fracturing can be most effective. …”
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An OFDM Signal Enhancement and Demodulation Method Based on Segmented Asymmetric Bistable Stochastic Resonance by Gaohui Liu, Xiaqiang Chu

“…The SABSR system is then applied to OFDM signal enhancement and demodulation, with SNR gain used as the optimization metric. The quantum particle swarm optimization algorithm is employed to fine-tune system parameters. …”
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Research on Viewpoints Planning for Industrial Robot-Based Three-Dimensional Sculpture Reconstruction by Zhen Zhang, Changcai Cui, Guanglin Qin, Hui Huang, Fangchen Yin

“…Subsequently, local viewpoint planning is conducted to refine regions that were incompletely captured in the initial step, with a genetic algorithm optimizing the scanning paths to enhance efficiency. …”
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Smoothing Photovoltaic Power Fluctuations for Cascade Hydro-PV-Pumped Storage Generation System Based on a Fuzzy CEEMDAN by Lei Chen, Jun Wang, Zhang Sun, Tao Huang, Fan Wu

“…Furthermore, in order to overcome the drawback that too frequent conversion of unit operating mode would reduce the service life and smoothing effect of the VSPSS unit, the optimization model of the base power of the VSPSS is established and solved by the grid adaptive direct search method (MADS) to obtain the control signal of the VSPSS for suppressing the short-term fluctuations of the PV output. …”
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Breast Morphology Recognition and Control Based on Uncalibrated Vision by Haiyan Du, Jianxin Li, Cheng Qian, Qiang Liu, Zhimeng Zhang

“…An improved algorithm combining stochastic Hough transform and direct least squares is proposed to enhance the accuracy of the target localization in the images. …”
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Advancements in machine learning for estimating parameters of wastewater treatment plants by Kolyeva Natalya, Rastyagaev Alexander, Kortenko Lyudmila, Rozhkov Sergey, Sbitneva Mariia, Kuznetsov Aleksandr

“…As a result of the study, a model of the XGBoost algorithm was developed, which successfully coped with the task of optimization of calculations, providing high accuracy, and this, in turn, opens up new opportunities for improving the efficiency of design of wastewater treatment plants.…”
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Automatic license-plate recognition by A. V. Poltavskii, T. G. Yurushkina, M. V. Yurushkin

“…Quality of the system is provided through the optimization of various models with different modifications. …”
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TKEO-Enhanced Machine Learning for Classification of Bearing Faults in Predictive Maintenance by Xuanbai Yu, Olivier Caspary

“…These findings offer new insights to support reliable predictive maintenance in industrial settings and provide a new perspective for future research into active vibration control, where vibration signal analysis, feature extraction, and mathematical modeling play key roles in optimizing control algorithms and enhancing the efficiency of adaptive control systems.…”
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Bagging Vs. Boosting in Ensemble Machine Learning? An Integrated Application to Fraud Risk Analysis in the Insurance Sector by Ruixing Ming, Osama Mohamad, Nisreen Innab, Mohamed Hanafy

“…Addressing the pressing challenge of insurance fraud, which significantly impacts financial losses and trust within the insurance industry, this study introduces an innovative automated detection system utilizing ensemble machine learning (EML) algorithms. The approach encompasses four strategic phases: 1) Tackling data imbalance through diverse re-sampling methods (Over-sampling, Under-sampling, and Hybrid); 2) Optimizing feature selection (Filtering, Wrapping, and Embedding) to enhance model accuracy; 3) employing binary classification techniques (Bagging and Boosting) for effective fraud identification; and 4) applying explanatory model analysis (Shapley Additive Explanations, Break-down plot, and variable-importance Measure) to evaluate the influence of individual features on model performance. …”
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Flexi-YOLO: A lightweight method for road crack detection in complex environments. by Jiexiang Yang, Renjie Tian, Zexing Zhou, Xingyue Tan, Pingyang He

“…Road crack detection is critical to global infrastructure maintenance and public safety, and complex background environments and nonlinear damage crack patterns challenge the need for real-time, efficient, and accurate detection.This paper proposes a lightweight yet robust Flexi-YOLO model based on the YOLOv8 algorithm. We designed Wise-IoU as the model's loss function to optimize the regression accuracy of its bounding boxes and enhance robustness to low-quality samples. …”
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Research on False Alarm Rate Reducing Strategies for Subway Train Fire Alarm System by ZHANG Qian, XU Shaohong, XUE Hongquan

“…The false alarm rate can be reduced by hardware optimization methods such as adding dust filter devices, adopting dual light source detectors, multi-parameter gas detectors and pyrolysis particle detectors; the rate can also be reduced by optimizing software algorithms (optimization modeling method, automatic adjustment of alarm thresholds, machine self-learning algorithm, etc.). …”
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Research on Measurement of Coal–Water Slurry Solid–Liquid Two-Phase Flow Based on a Coriolis Flow Meter and a Neural Network by Jie Liu, Lingfei Kong, Jiahao Ma, Xuemei Zhang, Chengjie Wang, Dongze Wu

“…The first correction results showed that the corrected error of the predictive model was 3.98%, a significant improvement compared to the 5.11% error measured by the X company’s meter. (2) Building on this, a second correction model was established through algorithm optimization, successfully reducing the corrected error of the predictive model to 1.01%. …”
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Sistem Kontrol Swarm untuk Flocking Wahana NR-Awak Quadrotor dengan Optimasi Algoritma Genetik by Endra Joelianto, Winarendra Satya Rajasa, Agus Samsi

“…The controller that is designed has many parameters, so the optimal parameter selection is very difficult. The search for optimal parameters in the swarm model controller requires optimization techniques such as the genetic algorithm (GA) to direct the search for solutions that produce the best performance. …”
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Data and Knowledge Dual-Driven Creep Life Prediction for Austenitic Heat-Resistance Steel by Xiaochang Xie, Mutong Liu, Ping Yang, Zenan Yang, Chengbo Pan, Chenchong Wang, Xiaolu Wei

“…In this study, we collected 216 creep data of austenitic heat-resistant steel, selected a variety of different machine learning algorithms to establish creep life prediction models, calculated and introduced a large amount of physical metallurgy knowledge highly related to creep based on Thermo-Calc, and converted the creep life into the form of the Larson–Miller parameter to optimize the data distribution, which effectively improved the prediction accuracy and interpretability of the model. …”
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A Dynamic Kalman Filtering Method for Multi-Object Fruit Tracking and Counting in Complex Orchards by Yaning Zhai, Ling Zhang, Xin Hu, Fanghu Yang, Yang Huang

“…By optimizing the network structure, the improved YOLO detection model provides high-quality detection results for subsequent tracking tasks. …”
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Multi-Source Attention U-Net: A Novel Deep Learning Framework for the Land Use and Soil Salinization Classification of Keriya Oasis in China with RADARSAT-2 and Landsat-8 Data by Yang Xiang, Ilyas Nurmemet, Xiaobo Lv, Xinru Yu, Aoxiang Gu, Aihepa Aihaiti, Shiqin Li

“…Moreover, the MS + SAR MSA-U-Net, in comparison to traditional machine learning methods and the baseline model, improved the OA and Kappa coefficient by 8.24% to 12.55% and 0.08 to 0.15, respectively. …”
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Research on the blockchain-based trusted ownership confirmation and value transfer system and its light weight of industrial data assets by WANG Dongchu, FU Yusun, YU Ya

“…The consensus protocol algorithm of the blockchain system was optimized based on the trustworthiness of nodes, reducing the probability of malicious attacks on nodes while improving the efficiency of system transaction consensus, achieving security and lightweight parallelism of the entire system. …”
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