Showing 4,901 - 4,920 results of 7,642 for search '(((improved OR improve) most) OR ((improved OR improve) model)) optimization algorithm', query time: 0.44s Refine Results
  1. 4901

    AgrUNet: A Multi-GPU UNet Based Model for Crops Classification by Andrea Miola, Enrico Calore, Sebastiano Fabio Schifano

    Published 2024-01-01
    “…Our model achieves a Dice score of approximately 0.90, a peak throughput of 59 and 605 /s for the train and inference steps respectively, improving by approximately a factor 7X the best results reported in the literature and quite ideal speedup running both on a 4X V100 and 8X A100 GPU systems.…”
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  2. 4902

    Enhancing Resilience and Efficiency in Power System: A Five-Level Dynamic Planning Model by Mahnaz Rezaei, Mohammad Tolou Askari, Meysam Amirahmadi, Vahid Ghods

    Published 2024-01-01
    “…Therefore, a five-level dynamic model is developed to improve resilience to natural disaster events. …”
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  3. 4903

    Research on Anomaly Detection Model for Power Consumption Data Based on Time-Series Reconstruction by Zhenghui Mao, Bijun Zhou, Jiaxuan Huang, Dandan Liu, Qiangqiang Yang

    Published 2024-09-01
    “…Compared with commonly used algorithms, the proposed algorithm improved precision by 2.2%, recall by 12.1%, and F1 score by 7.7%, outperforming conventional anomaly detection algorithms.…”
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  4. 4904

    GA-Synthesized Training Framework for Adaptive Neuro-Fuzzy PID Control in High-Precision SPAD Thermal Management by Mingjun Kuang, Qingwen Hou, Jindong Wang, Jianping Guo, Zhengjun Wei

    Published 2025-07-01
    “…The controller maintains stability under structural perturbations and abrupt thermal disturbances without the need for offline retuning, owing to the real-time inference capabilities of the ANFIS model. By combining global evolutionary optimization with intelligent online adaptation, this approach improves both accuracy and generalization, offering a practical and scalable solution for SPAD thermal management in demanding environments such as quantum communication, sensing, and single-photon detection platforms.…”
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  5. 4905

    EUR Prediction for Shale Gas Wells Based on the ROA-CatBoost-AM Model by Weikang He, Xizhe Li, Yujin Wan, Honming Zhan, Nan Wan, Sijie He, Yaoqiang Lin, Longyi Wang, Wenxuan Yu, Liqing Chen

    Published 2025-02-01
    “…The hyperparameters of the model were optimized using the Rabbit Optimization Algorithm (ROA), and 10-fold cross-validation was employed to improve the stability and reliability of model evaluation, mitigating overfitting and bias. …”
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  6. 4906

    Experimental acoustic study of small horizontal axis wind turbines based on computational fluid dynamics and artificial intelligence approaches by M. Sadeghi malekabadi, A.R. Davari

    Published 2024-12-01
    “…However, the extensive numerical computations required for accurate evaluation often hinder the implementation of multi-objective optimization strategies. This paper introduces an innovative approach to address this issue, leveraging a combination of neural network-based reduced order modeling and a multi-objective genetic algorithm. …”
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  7. 4907

    Advances in Miniaturized Computational Spectrometers by Qian Xue, Yang Yang, Wenkai Ma, Hanqiu Zhang, Daoli Zhang, Xinzheng Lan, Liang Gao, Jianbing Zhang, Jiang Tang

    Published 2024-12-01
    “…The reconstruction algorithms are classified into traditional and deep learning algorithms, and they are carefully analyzed based on the mathematical models required for spectral reconstruction. …”
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  8. 4908

    IDHNet: Ultra‐Short‐Term Wind Power Forecasting With IVMD–DCInformer–HSSA Network by Wei Li, Lu Gao, Fei Zhang, XiaoYing Ren, Ling Qin

    Published 2024-12-01
    “…Subsequently, the Sparrow search algorithm (HSSA) is employed to optimize the parameters of the enhanced Informer deep neural network, which are then integrated into the improved Informer model. …”
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  9. 4909

    A Particle Swarm Optimization-Based Ensemble Broad Learning System for Intelligent Fault Diagnosis in Safety-Critical Energy Systems with High-Dimensional Small Samples by Jiasheng Yan, Yang Sui, Tao Dai

    Published 2025-02-01
    “…To address the aforementioned challenge, this paper proposes an innovative IFD method for SCES that combines the particle swarm optimization (PSO) algorithm and the ensemble broad learning system (EBLS). …”
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  10. 4910

    Research on Centroid Localization Method of Underground Space Ground Electrode Current Field Based on RSSI by Sirui Chu, Hui Zhao, Zhong Su, Xiangxian Yao, Xibing Gu, Yanke Wang, Zhongao Ling

    Published 2025-05-01
    “…On this basis, an improved weighted centroid localization algorithm is introduced to improve the localization accuracy and reliability by optimizing the algorithm parameters to cope with the fluctuations and instabilities generated in the signal propagation process. …”
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  11. 4911

    Explainable Machine Learning Models for Colorectal Cancer Prediction Using Clinical Laboratory Data by Rui Li MS, Xiaoyan Hao MS, Yanjun Diao MD, Liu Yang MS, Jiayun Liu MD

    Published 2025-04-01
    “…Incorporating stool miR-92a detection into the model further improved diagnostic performance. Shapley additive explanations (SHAP) plots indicated that FOBT, CEA, lymphocyte percentage (LYMPH%), and hematocrit (HCT) were the most significant features contributing to CRC diagnosis. …”
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  12. 4912

    Dynamic Inversion Method for Concrete Gravity Dam on Soft Rock Foundation by Guanglin Yin, Chaoning Lin, Taozhen Sheng, Wenbo Xue, Tongchun Li, Siyu Chen

    Published 2025-04-01
    “…To address this limitation, an improved particle swarm optimization (PSO) algorithm is developed for dynamic parameter inversion, combining real-time monitoring data with finite element modeling to evaluate the time-varying elastic modulus of the foundation. …”
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  13. 4913

    Heat recovery integration in a hybrid geothermal-based system producing power and heating using machine learning approach to maximize outputs by Hatem Gasmi, Azher M. Abed, Ashit Kumar Dutta, Fahad M. Alhomayani, Ibrahim Mahariq, Fahad Alturise, Salem Alkhalaf, Tamim Alkhalifah, Yasser Elmasry, Baseem Khan

    Published 2024-11-01
    “…This study offers an in-depth thermodynamic analysis and optimization of an integrated renewable energy system that merges a double-flash geothermal system with a transcritical carbon dioxide Rankine cycle, utilizing machine learning algorithms. …”
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  14. 4914

    An ensemble time-embedded transformer model for traffic conflict prediction at RRFB pedestrian crossings by Md Jamil Ahsan, Mohamed Abdel-Aty, B M Tazbiul Hassan Anik, Zubayer Islam

    Published 2025-06-01
    “…For improved performance, these models were then combined using a voting classifier technique. …”
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  15. 4915

    Implementing Large Language Models in Health Care: Clinician-Focused Review With Interactive Guideline by HongYi Li, Jun-Fen Fu, Andre Python

    Published 2025-07-01
    “…General-purpose LLMs may not perform well in specialized areas as they often require lightweight prompt engineering methods or fine-tuning techniques based on specific datasets to improve model performance. Most LLMs with multimodal abilities are closed-source models and, therefore, lack of transparency, model customization, and fine-tuning for specific clinical tasks and may also pose challenges regarding data protection and privacy, which are common requirements in clinical settings. …”
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  16. 4916

    Machine learning-based analysis on pharmaceutical compounds interaction with polymer to estimate drug solubility in formulations by Ahmad J. Obaidullah, Wael A. Mahdi

    Published 2025-07-01
    “…Three base models were evaluated including: Decision Tree (DT), K-Nearest Neighbors (KNN), and Multilayer Perceptron (MLP), which are subsequently improved with the AdaBoost ensemble method. …”
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  17. 4917

    Research on intelligent computing offloading model based on reputation value in mobile edge computing by Jin QI, Hairong SUN, Kun GONG, Bin XU, Shunyi ZHANG, Yanfei SUN

    Published 2020-07-01
    “…Aiming at the problem of high-latency,high-energy-consumption,and low-reliability mobile caused by computing-intensive and delay-sensitive emerging mobile applications in the explosive growth of IoT smart mobile terminals in the mobile edge computing environment,an offload decision-making model where delay and energy consumption were comprehensively included,and a computing resource game allocation model based on reputation that took into account was proposed,then improved particle swarm algorithm and the method of Lagrange multipliers were used respectively to solve models.Simulation results show that the proposed method can meet the service requirements of emerging intelligent applications for low latency,low energy consumption and high reliability,and effectively implement the overall optimized allocation of computing offload resources.…”
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  18. 4918

    Strategic Integration of Battery Energy Storage Systems for Effective EV Charging Demand Management in Transactive Energy Markets by T. H. M. Sumon Rashid, Md. Rabiul Islam, Md Muminur Rahman Sonic

    Published 2025-01-01
    “…Using the DIgSILENT PowerFactory power system software for modeling and simulation, the active and reactive power dispatch of BESS is optimized via a differential evolution (DE) algorithm. …”
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  19. 4919

    A carbon aware ant colony system for the sustainable generalized traveling salesman problem by Marina Lin, Laura P. Schaposnik

    Published 2025-07-01
    “…By integrating sustainability into transportation models, the CAACS Algorithm is a powerful tool for real-world applications, including network design, delivery route planning, and commercial aircraft logistics. …”
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  20. 4920

    Development of a machine learning-based surrogate model for friction prediction in textured journal bearings by Yujun Wang, Georg Jacobs, Shuo Zhang, Benjamin Klinghart, Florian König

    Published 2025-07-01
    “…This enhancement is achieved through an architecture design based on cross-validation and further optimization utilizing the genetic algorithm. Eventually, the average prediction accuracy is improved to 98.81% from 95.89%, with the maximum error reduced to 3.25% from 13.17%. …”
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