Error-Index-Based Algorithm for Low-Velocity Impact Localization by Tao Peng, Lilin Cui, Xiufeng Huang, Wenjing Yu, Rongwu Xu

“…The results indicated that the proposed localization algorithm can accurately locate the impact points on a flat plate and cylindrical shell, even under strong background noise conditions, providing a reference for future research on locating low-velocity impact points in large equipment.…”
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Improved SOM algorithm for damage characterization based on visual sensing by Hongtao Zhu, Shuyun Guo

“…To enhance the accuracy and efficiency of concrete damage identification, this research proposes an improved Self-Organizing Map algorithm based on visual sensing. …”
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Abnormal link detection algorithm based on semi-local structure by Haoran SHI, Lixin JI, Shuxin LIU, Gengrun WANG

“…With the research in network science, real networks involved are becoming more and more extensive.Redundant error relationships in complex systems, or behaviors that occur deliberately for unusual purposes, such as wrong clicks on webpages, telecommunication network spying calls, have a significant impact on the analysis work based on network structure.As an important branch of graph anomaly detection, anomalous edge recognition in complex networks aims to identify abnormal edges in network structures caused by human fabrication or data collection errors.Existing methods mainly start from the perspective of structural similarity, and use the connected structure between nodes to evaluate the abnormal degree of edge connection, which easily leads to the decomposition of the network structure, and the detection accuracy is greatly affected by the network type.In response to this problem, a CNSCL algorithm was proposed, which calculated the node importance at the semi-local structure scale, analyzed different types of local structures, and quantified the contribution of edges to the overall network connectivity according to the semi-local centrality in different structures, and quantified the reliability of the edge connection by combining with the difference of node structure similarity.Since the connected edges need to be removed in the calculation process to measure the impact on the overall connectivity of the network, there was a problem that the importance of nodes needed to be repeatedly calculated.Therefore, in the calculation process, the proposed algorithm also designs a dynamic update method to reduce the computational complexity of the algorithm, so that it could be applied to large-scale networks.Compared with the existing methods on 7 real networks with different structural tightness, the experimental results show that the method has higher detection accuracy than the benchmark method under the AUC measure, and under the condition of network sparse or missing, It can still maintain a relatively stable recognition accuracy.…”
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Analyzing greedy vaccine allocation algorithms for metapopulation disease models. by Jeffrey Keithley, Akash Choudhuri, Bijaya Adhikari, Sriram V Pemmaraju

“…We provide a theoretical explanation for this effectiveness by showing that the approximation factor (a measure of how well the algorithmic output for a problem instance compares to its theoretical optimum) of these algorithms depends on the submodularity ratio of the objective function g. …”
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Predicting Quail Egg Quality Using Machine Learning Algorithms by BI Yildiz, K Eskioğlu, D Özdemir, M Akşit

“…ABSTRACT This study evaluates the effectiveness of machine learning algorithms in predicting quail egg quality based on nine key parameters, including egg weight, egg width, egg length, yolk height, yolk width, yolk weight, albumen height, albumen width, and albumen length. …”
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Tennis Assistance Technology Based on Dynamic Time Warping Algorithm by Penggang Wang, Pengpeng Zhang, Guanxi Fan

“…Traditional teaching methods are inefficient and difficult to quantify the correctness of actions. In view of this research, a tennis sports assistance technology based on dynamic time warping algorithm is developed. …”
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Detection of Plants Leaf Diseases using Swarm Optimization Algorithms by Saud Abdul Razzaq, Baydaa Khaleel

“…The results obtained from these three algorithms were compared and the proposed method (PSO-CSO) obtained the best results compared to the two methods. …”
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An Adaptive Chaotic Sine Cosine Algorithm for Constrained and Unconstrained Optimization by Yetao Ji, Jiaze Tu, Hanfeng Zhou, Wenyong Gui, Guoxi Liang, Huiling Chen, Mingjing Wang

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Digital asset management in a Digital environment: algorithms and services by I.  M. Stepnov, М.  A.  Fedotova

“…For this purpose, authors compared the classical approach to value-based management (based on value levers) with the recommendation algorithms which is growing trend for active use. …”
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Prediction of high-risk pregnancy based on machine learning algorithms by Xinyu Pi, Junzhi Wang, Liangliang Chu, Guochun Zhang, Wenli Zhang

“…It is worth noting that MLP demonstrates superior performance compared with the other five algorithms. By applying the MLP method, the study successfully established an efficient pregnancy risk prediction model. …”
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Design and experiment of landslide monitoring algorithm based on MEMS sensor by Di WU, Taiming LIANG, Jing WU, Jianjian WU, Yang YI, Wanpeng LOU

“…MEMS technology was used to monitor the internal displacement of the soil for the test slopes, and the results were compared with the the finite element simulation outputs to evaluate the accuracy and reliability of the algorithm. …”
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Lightweight insulator target detection algorithm based on improved YOLOX by Bing Zeng, Wei Hua, Dezhi Li, Zhihao Zhou, Hao Wan, Yunmin Xie, Tangbing Li, Yucong Chen, Jianglei Li, Shenli Wang, Shixun Fu, Zihan Jin, Wenhua Zhang

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Prediction of mung bean production using machine learning algorithms by Azanu Mirolgn Mequanenit, Aleka Melese Ayalew, Ayodeji Olalekan Salau, Eyerusalem Alebachew Nibret, Million Meshesha

“…To achieve the objective of this study, different experiments were conducted using Random Forest, Gradient Boosting, and Xgboosting algorithms. In addition, the predictive performances of the classifiers are evaluated and compared using accuracy, precision, recall, F1-score, and confusion matrix. …”
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ALGORITHM OF PSYCHOLOGICAL AND PSYCHOTHERAPEUTIC SUPPORT OF PATIENTS WITH CHRONIC CEREBRAL ISCHEMIA by I. V. Khianikiainen, V. A. Mikhailov

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Earthworm optimization algorithm for extracting parameters for solar cells and photovoltaic modules by Fatima Wardi, Mohamed Louzazni, Mohamed Hanine

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Quantum approximate optimization algorithms for maximum cut on low-girth graphs by Tongyang Li, Yuexin Su, Ziyi Yang, Shengyu Zhang

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Supraharmonics monitoring based on VSSESP-DBP dynamic compressed sensing algorithm by Chao Yan, Hongtao Shen, Jie Yu, Peng Tao, Hongxi Wang, Ting Yang

“…These findings highlight the potential of the method for real-time power quality monitoring applications. Future research could focus on optimizing algorithm parameters for different grid conditions and extending the approach to broader power quality disturbances.…”
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Medical Images Segmentation Based on Unsupervised Algorithms: A Review by Revella E. A. Armya, Adnan Mohsin Abdulazeez

“…The key aim of this paper is to study some literature on unsupervised algorithms (K-mean, K-medoids) and to compare the working efficiency of unsupervised algorithms with different types of medical images. …”
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Algorithms for Routing Optimization in Multipoint to Multipoint 4PL System by Jia Li, Yanqiu Liu, Ying Zhang, Shida Xu

“…The experimental result is compared with the Enumeration Algorithm (EA), and it shows that this algorithm can find the satisfactory solution and is a powerful optimization method for solving the problem.…”
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MGL-YOLO: A Lightweight Barcode Target Detection Algorithm by Yuanhao Qu, Fengshou Zhang

“…Experimental results show that the proposed algorithm increases MAP50 and MAP50.95 by 2.57% and 2.31%, respectively, compared to YOLOv8, while reducing parameter size and computational cost by 36.21% and 34.15%, respectively. …”
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