Deep learning-based recognition model of football player’s technical action behavior using PCA–LBP algorithm by Hongtao Chen, Zhengbai Lin, Quan Xu

“…The PCA–LBP algorithm also has higher recognition accuracy when comparing dribbling, stopping, and fake action. …”
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Optimizing Cancer Detection: Swarm Algorithms Combined with Deep Learning in Colon and Lung Cancer using Biomedical Images by HariKrishna Pathipati, Lova Naga Babu Ramisetti, Desidi Narsimha Reddy, Swetha Pesaru, Mashetty Balakrishna, Thota Anitha

“…Eventually, the whale optimization algorithm (WOA) is used to optimally choose the hyperparameters of the CNN‐BiGRU model. …”
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Spiking Neural Networks Optimized by Improved Cuckoo Search Algorithm: A Model for Financial Time Series Forecasting by Panke Qin, Yongjie Ding, Ya Li, Bo Ye, Zhenlun Gao, Yaxing Liu, Zhongqi Cai, Haoran Qi

“…To address the performance limitations of Spiking Neural Networks (SNNs) caused by hyperparameter sensitivity, this study proposes an SNN model optimized by an Improved Cuckoo Search (ICS) algorithm (termed ICS-SNN). The ICS algorithm enhances global search capability through piecewise-mapping-based population initialization and introduces a dynamic discovery probability mechanism that adaptively increases with iteration rounds, thereby balancing exploration and exploitation. …”
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Study on Short Term Temperature Forecast Model in Jiangxi Province based on LightGBM Machine Learning Algorithm by Kanghui SUN, An XIAO, Houjie XIA

“…In order to achieve further improvement in the forecast accuracy of station temperatures and enhance the forecast capability for extreme temperatures， this study establishes a 24-hour national station daily maximum （minimum） temperature forecast model for Jiangxi Province based on the LightGBM machine-learning algorithm and the MOS forecast framework by using the surface observation data of 91 national stations in Jiangxi Province and the upper-air and surface forecast data of the ECMWF model from 2017 to 2019.The results of the 2020 evaluation show that the LightGBM model daily maximum （minimum） temperature forecast is consistent with the observed trend， and the annual average forecast is better than that of three numerical models， ECMWF， CMA-SH9 and CMA-GFS， two machine learning products， RF and SVM， and subjective revision products.In terms of the spatial and temporal distribution of forecast errors， the model's daily maximum （minimum） temperature forecast errors in winter and spring are slightly larger than those in summer and autumn； the daily maximum temperature forecast errors show the spatial distribution characteristics of "larger in the south and smaller in the north， and larger in the periphery than in the centre"， while the opposite is true for the daily minimum temperatures.In terms of important weather processes， the LightGBM model has the best prediction effect among the seven products in the high temperature process； in the strong cold air process， the LightGBM model is still better than the three numerical model products and the other two machine-learning models， but the prediction effect of the daily minimum temperature is not as good as that of the subjective revision products.After a simple empirical correction for the low-temperature forecast error in the strong cold air process， the model low-temperature forecast effect is close to that of the subjective revision product.The model significance analysis shows that the recent surface observation features also contribute to the model construction， and the results can be used as a reference for model improvement and temperature forecast product development.At present， the LightGBM model temperature forecast products have been applied to meteorological operations in Jiangxi Province.…”
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Electrical Equivalent Circuit Parameter Estimation of Commercial Induction Machines Using an Enhanced Grey Wolf Optimization Algorithm by Premkumar Manoharan, Sowmya Ravichandran, Jagarapu S. V. Siva Kumar, Mustafa Abdullah, Tan Ching Sin, Tengku Juhana Tengku Hashim

“…Comparative analyses reveal that AWGWO outperforms existing algorithms not only in achieving lower error rates, but also in maintaining stability. …”
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A Low-Complexity Path-Planning Algorithm for Multiple USVs in Task Planning Based on the Visibility Graph Method by Kai Xue, Zhiqin Huang, Ping Wang, Zeyu Xu, Decheng Kong

“…After that, the Dijkstra algorithm is employed to find the shortest path from each start point to all target points, also with the low-complexity <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mi>O</mi><mfenced><mi>n</mi></mfenced></mrow></semantics></math></inline-formula>. …”
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S&#x2082;Head: Small-Scale Human Head Detection Algorithm by Improved YOLOv8n Architecture by Yuteng Sui, Xinghua Shan, Linlin Dai, Hui Jing, Bo Li, Jianjun Ma

“…To address this, we propose a novel lightweight head detection algorithm named S2Head, based on an improved YOLOv8n framework. …”
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Research on fast warning algorithm of SF6 circuit breaker gas leakage under high voltage decomposition by ZHANG Jianglu, WU Chao, YUE Yonggang, ZHAI Chunyu, WU Jianling, FANG Guobao

“…Therefore, a study on the rapid early warning algorithm for SF6 circuit breaker gas leakage under high voltage decomposition is proposed. …”
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UAV Real-Time Target Detection and Tracking Algorithm Based on Improved KCF and YOLOv5s_MSES by Shihai Cao, Ting Wang, Tao Li, Shumin Fei

“…To sum up, the proposed algorithm not only achieves the ideal tracking effect, but also meets the real-time requirement with higher precision, which means that the comprehensive performance is superior to some existing methods.…”
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Mapping climate change induced forest fire susceptibility using tree-based machine learning algorithms in Bangladesh by Mafrid Haydar, Al Hossain Rafi, Md.Kamran Hasan Khan, Sakib Hosan, Halima Sadia

“…This study employs tree-based machine learning (ML) algorithms to assess Forest Fire Susceptibility in the Chittagong Hill Tracts (CHT) of Bangladesh under current and anticipated climate change scenarios. …”
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Automated Audit and Self-Correction Algorithm for Seg-Hallucination Using MeshCNN-Based On-Demand Generative AI by Sihwan Kim, Changmin Park, Gwanghyeon Jeon, Seohee Kim, Jong Hyo Kim

“…This study not only enhances the efficiency and reliability of handling the Seg-Hallucination but also eliminates the reliance on ground truth. The ASHSC algorithm offers intuitive 3D guidance for uncertainty regions, while maintaining manageable computational complexity. …”
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IMPLEMENTATION OF THE DBSCAN ALGORITHM FOR CLUSTERING STUNTING PREVALENCE TYPOLOGY IN WEST JAVA, CENTRAL JAVA, AND EAST JAVA REGIONS by Bagus Sumargo, Kadir Kadir, Dena Safariza, Munawar Asikin, Dania Siregar, Nilam Novita Sari, Danu Umbara, Rizky Hilmianto, Robert Kurniawan, Irman Firmansyah

“…The distance obtained then was used in the KNN algorithm to determine eps and MinPts parameters. Clustering is done using standardized data and DBSCAN parameters obtained from the k-dist plot, eps is 1.92, and MinPts is 2. …”
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Seasonal forecasting of the hourly electricity demand applying machine and deep learning algorithms impact analysis of different factors by Heba-Allah Ibrahim El-Azab, R. A. Swief, Noha H. El-Amary, H. K. Temraz

“…Precision improvements are also considered when creating a model. Where the whole database is split into four seasons based on demand patterns. …”
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Efficacy of two radiographic algorithms for detection of peri-implant bone defects on cone-beam computed tomography scans by Faezeh Yousefi, Ali Heidari, Azita Ehsani, Maryam Farhadian, Marzieh Ehsani

“…By the advances in cone-beam computed tomography (CBCT) scanners and introduction of new algorithms, it is important to find the most efficient protocol for detection of bone defects. …”
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Analysis of phenotypic manifestations of connective tissue dysplasia in adult patients with osteogenesis imperfecta and development of a diagnostic algorithm by D. I. Valeeva, R. I. Khusainova, L. N. Khusainova, M. M. Khafizov, A. V. Tyurin

“…In type III, spinal deformities are characteristic, chest deformities were more often observed in patients with type V OI. A clinical algorithm for determining OI types was developed to optimize diagnostics and genotyping.…”
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Ultra-Broadband, Fabrication Tolerant Optical Coupler for Arbitrary Splitting Ratio Using Particle Swarm Optimization Algorithm by Lemeng Leng, Minfeng Jin, Zhongzhi Lin, Chenbin Zhang, Ding Ding, Wei Jiang

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Knowledge reasoning and strategy optimization for ship operation and maintenance based on digital twin and improved KD tree algorithm by Liyao ZHANG, Ziqian GUO, Ruifang LI, Xun YE, Tao MA

“…ResultsThe experimental results show that the proposed improved KD tree algorithm (ω-KDtree-WOA) achieves an inference accuracy of 0.928 when the K value is 4 and the population size is 400, which is approximately 3.2% higher than that of the traditional KD tree algorithm under the same conditions. …”
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Application of Machine Learning Algorithms for Predicting the Dynamic Stiffness of Rail Pads Based on Static Stiffness and Operating Conditions by Isaac Rivas, Jose A. Sainz-Aja, Diego Ferreño, Víctor Calzada, Isidro Carrascal, Jose Casado, Soraya Diego

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From Crisis to Algorithm: Credit Delinquency Prediction in Peru Under Critical External Factors Using Machine Learning by Jomark Noriega, Luis Rivera, Jorge Castañeda, José Herrera

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A Computable Phenotype Algorithm for Postvaccination Myocarditis/Pericarditis Detection Using Real-World Data: Validation Study by Matthew Deady, Raymond Duncan, Matthew Sonesen, Renier Estiandan, Kelly Stimpert, Sylvia Cho, Jeffrey Beers, Brian Goodness, Lance Daniel Jones, Richard Forshee, Steven A Anderson, Hussein Ezzeldin

“…These findings underscore the algorithm's capability for real-time detection of AEs, though they also highlight variability in performance across different health care systems. …”
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