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  1. 1841

    Carbon market and emission reduction: evidence from evolutionary game and machine learning by Keyang Zhan, Zhengning Pu

    Published 2025-04-01
    “…This paper establishes an evolutionary game model to analyze the interaction between the government and enterprises and applies the Gradient Boosting Decision Tree (GBDT) algorithm to identify carbon emission reduction effects of the carbon market based on carbon emission data from 2000 to 2019. …”
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    Article
  2. 1842

    Optimization Study of Centrifugal Fan Volute Parameters based on Non-dominated Sorting Genetic Algorithm III Algorithm by J. L. Li, X. J. Wang, H. Gong, J. J. Wang

    Published 2025-08-01
    “…An efficient and accurate BP neural network was established as a surrogate model for predicting volute performance, and optimal design parameter combinations were obtained using the NSGA-III algorithm. …”
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    Article
  3. 1843

    MR Image Based Approach for Metal Artifact Reduction in X-Ray CT by Andras Anderla, Dubravko Culibrk, Gaspar Delso, Milan Mirkovic

    Published 2013-01-01
    “…In this paper, we propose a new method for metal-artifact reduction using complementary magnetic resonance (MR) images. …”
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    Article
  4. 1844

    PID Control and Input Shaping for Quadrotor UAV Stabilization and Payload Swing Reduction by Liyana Ramli, Izzuddin M. Lazim, Amalin Aisya Awi, Aina Syazwin Shukor

    Published 2025-06-01
    “…Simulation results demonstrate that the proposed control scheme achieves a substantial reduction in payload swing of at least 65.28% compared to existing methods. …”
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    Article
  5. 1845

    Dimensionality Reduction and Clustering Strategies for Label Propagation in Partial Discharge Data Sets by Ronaldo F. Zampolo, Frederico H. R. Lopes, Rodrigo M. S. de Oliveira, Martim F. Fernandes, Victor Dmitriev

    Published 2024-11-01
    “…In this work, we propose a label propagation algorithm applied to PRPD data sets, aiming to reduce the time necessary to manually label PRPDs. …”
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  6. 1846
  7. 1847

    An external validation of the QCOVID3 risk prediction algorithm for risk of hospitalisation and death from COVID-19: An observational, prospective cohort study of 1.66m vaccinated adults in Wales, UK. by Jane Lyons, Vahé Nafilyan, Ashley Akbari, Stuart Bedston, Ewen Harrison, Andrew Hayward, Julia Hippisley-Cox, Frank Kee, Kamlesh Khunti, Shamim Rahman, Aziz Sheikh, Fatemeh Torabi, Ronan A Lyons

    Published 2023-01-01
    “…<h4>Introduction</h4>At the start of the COVID-19 pandemic there was an urgent need to identify individuals at highest risk of severe outcomes, such as hospitalisation and death following infection. The QCOVID risk prediction algorithms emerged as key tools in facilitating this which were further developed during the second wave of the COVID-19 pandemic to identify groups of people at highest risk of severe COVID-19 related outcomes following one or two doses of vaccine.…”
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  8. 1848
  9. 1849
  10. 1850

    Integrated Planning for Shared Electric Vehicle System Considering Carbon Emission Reduction by Xiaohui Sun, Yumei Mi, Askar Ahtam, Zhi Zuo

    Published 2024-12-01
    “…By applying these models to the Chicago Sketch network and using a genetic algorithm to solve the models, it is concluded that the optimal outlet location solution considering carbon emission reduction will increase the outlet construction cost and user travel time cost. …”
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    Article
  11. 1851

    MOMOS: The Multi-Object MKID Optical Spectrometer Simulator and Data Reduction Package by Crystal S. Kim, John I. Bailey III, Ronald A. López, W. Hawkins Clay, Benjamin A. Mazin

    Published 2025-01-01
    “…Treating simulator products as inputs, an algorithm was developed and implemented in the MOMOS data reduction package to calibrate and extract spectra.…”
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  12. 1852
  13. 1853

    Efficient Ensemble Learning-Based Models for Plastic Hinge Length Prediction of Reinforced Concrete Shear Walls by Naser Safaeian Hamzehkolaei, Mohammad Sadegh Barkhordari

    Published 2024-07-01
    “…This study aims to develop practical machine-learning (ML) models for PHL prediction of RCSWs. For this purpose, 721 data of nonplanar and rectangular RCSWs were utilized. …”
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    Article
  14. 1854

    Analysis of software methods for metal computed tomography artifact reduction: experimental research by A. V. Petraikin, Yu. A. Vasilev, Z. R. Artyukova, A. K. Smorchkova, D. S. Semenov, А. А. Baulin, A. A. Alikhanov, R. A. Erizhokov, O. V. Omelyanskaya

    Published 2024-12-01
    “…It was also shown that O‑MAR forms additional artifacts near the HJE.Conclusion. Metal artifact reduction algorithms do not distort the X‑ray density without an artifact source. …”
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  15. 1855
  16. 1856

    PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems by Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, Huiting ZHOU, Hong LUO

    Published 2022-07-01
    “…Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model, a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed, and a system model of fusion technology was designed.Through simulation comparison with other literature methods, it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability, but the algorithm implementation complexity was too high.Therefore, a complementary SLM-Clipping fusion solution was proposed, and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method, the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system, and greatly improves the computational efficiency.…”
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    Article
  17. 1857

    PAPR optimization based on SLM and PTS algorithms in NC-OFDM systems by Jie ZHOU, Bernardo Esono Esono Mikue, Xueying WANG, Huiting ZHOU, Hong LUO

    Published 2022-07-01
    “…Based on the non-continuous orthogonal frequency division multiplexing (NC-OFDM) model, a fusion optimization technology based on selected mapping (SLM) algorithm and partial transmit sequence (PTS) algorithm was proposed, and a system model of fusion technology was designed.Through simulation comparison with other literature methods, it was verified that the SLM-PTS fusion technology had excellent peak to average power ratio (PAPR) reduction ability, but the algorithm implementation complexity was too high.Therefore, a complementary SLM-Clipping fusion solution was proposed, and the deep learning method PAPRnet model was construted.The simulation results verif that prove the effectiveness of the method, the algorithm has an excellent PAPR suppressed effect on the NC-OFDM system, and greatly improves the computational efficiency.…”
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    Article
  18. 1858

    Advanced Classifiers and Feature Reduction for Accurate Insomnia Detection Using Multimodal Dataset by Ameya Chatur, Mostafa Haghi, Nagarajan Ganapathy, Nima TaheriNejad, Ralf Seepold, Natividad Martinez Madrid

    Published 2024-01-01
    “…Our findings emphasize the importance of tailoring feature sets and employing appropriate reduction techniques for optimal predictive modeling in sleep-related studies. …”
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  19. 1859

    Efficient Machine Learning Model for DDoS Detection System Based on Dimensionality Reduction by Saad Ahmed Dheyab, Shaymaa Mohammed Abdulameer, Salama Mostafa

    Published 2022-12-01
    “…This model relies mainly on dimensionality reduction and machine learning algorithms. The principal component analysis (PCA) and the linear discriminant analysis (LDA) techniques perform the dimensionality reduction in individual and hybrid modes to process and improve the data. …”
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  20. 1860

    Low-Complexity Distortionless Techniques for Peak Power Reduction in OFDM Communication Systems by A. Ghassemi, T. A. Gulliver

    Published 2012-01-01
    “…The three most effective distortionless techniques for PAPR reduction are partial transmit sequence (PTS), selective mapping (SLM), and tone reservation (TR). …”
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