Showing 1,201 - 1,220 results of 7,873 for search 'comparative research algorithm', query time: 0.15s Refine Results
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    Evaluation Method for Running State of Electricity Meters Based on Random Matrix Theory and Clustering Algorithm by Yingying CHENG, Jie DU, Quan ZHOU, Jiaming ZHANG, Xiaoyong ZHANG, Gang LI

    Published 2020-11-01
    “…The experiments show that compared with the traditional Principal Component Analysis evaluation method, the proposed method has good robustness, reliability and timeliness, which provides a new idea for the application research of power grid detection technology.…”
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    EnrichKit: a multi-omics tool for livestock research by Lihe Liu, Francisco Peñagaricano

    Published 2025-05-01
    “…Its tailored approach for species-specific analysis, combined with a comprehensive computational framework, positions it as a valuable tool for researchers. The potential of EnrichKit to transform livestock genomics research is evident, opening avenues for future enhancements and broader applications in the livestock omics research field.…”
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    Comparative Analysis of Machine Learning Techniques for Prediction of the Compressive Strength of Field Concrete by Omobolaji Opafola, Abisola Olayiwola, Ositola Osifeko, Adekunle David, Ajibola Oyedejı

    Published 2024-08-01
    “…Machine learning (ML) algorithms offer an alternative and this study presents a comparative analysis of five ML regression models; Gradient Boosting (GB), Random Forest (RF), Decision Tree (DT), K-Nearest Neighbors (KNN), and Linear Regression (LR) on a dataset of 1030 concrete samples. …”
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    Optimization of Relay Node Deployment in Wireless Sensor Communication Networks Based on IGA-RNDP Algorithm by Shubo Xu, Cheng Zhong

    Published 2025-01-01
    “…In large-scale network environments, the research method deployed the fewest number of relay nodes and had a concentrated distribution, with statistically significant differences compared to other algorithms. …”
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    AI optimization algorithms enhance higher education management and personalized teaching through empirical analysis by XiWen Xu

    Published 2025-03-01
    “…An empirical study conducted over one academic semester shows significant improvements in students’ learning outcomes, engagement, satisfaction, and efficiency when using AI-driven personalized teaching compared to traditional approaches. The research also identifies challenges and limitations, including data privacy issues, algorithmic bias, and the need for human-AI interaction. …”
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