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  1. 4861

    Increasing Minority Recall Support Vector Machine Model for Imbalanced Data Classification by Chunye Wu, Nan Wang, Yu Wang

    Published 2021-01-01
    “…In the experiments, the effects of different parameters on the performance of the algorithm were analyzed, and the optimal parameters for a recall rate of 1 were determined. …”
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    Article
  2. 4862

    A Hybrid Deep Learning Model for UAV Path Planning in Dynamic Environments by Junchi Zhang, Yanning Xian, Xun Zhu, Hongtao Deng

    Published 2025-01-01
    “…However, the commonly used Rapidly-exploring Random Tree (RRT) algorithm for UAV path planning often generates suboptimal paths that require extensive post-processing to improve. …”
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  3. 4863

    Research on AIGC Technology Driven Innovation Models and Risk Management in the Financial Sector by Gong Lipeng

    Published 2025-01-01
    “…Finally, this article proposes strategies such as improving the regulatory system, optimizing algorithm transparency, and strengthening data governance to promote the healthy development of AIGC technology in the financial sector.…”
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  4. 4864

    Research on the On-Line Identification of Ship Maneuvering Motion Model Parameters and Adaptive Control by Jinlai Liu, Lubin Chang, Luping Xu, Fang He, Yixiong He

    Published 2025-04-01
    “…A response-type ship maneuvering model is used, with a forgetting factor incorporated into the recursive least squares (RLS) algorithm based on the iterative least squares (ILS) method. …”
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  5. 4865

    FUR-DETR: A Lightweight Detection Model for Fixed-Wing UAV Recovery by Yu Yao, Jun Wu, Yisheng Hao, Zhen Huang, Zixuan Yin, Jiajing Xu, Honglin Chen, Jiahua Pi

    Published 2025-05-01
    “…Therefore, this paper proposes a lightweight visual detection model based on transformer architecture to further optimize computational efficiency. …”
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  6. 4866

    MetaStackD A robust meta learning based deep ensemble model for prediction of sensors battery life in IoE environment by D. Gayathri, S. P. Shantharajah

    Published 2025-04-01
    “…Leveraging regression algorithms such as Random Forest, Gradient Boosting, Light Gradient Boosting, Categorical Boosting and Extreme Gradient Boosting, we have modeled the non-linear and temporal dynamics of sensor battery degradation, thereby enabling proactive maintenance strategies, dynamic energy management, and resource allocation. …”
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  7. 4867

    Modeling the Dynamic Evolution of the Vehicular Ad Hoc Networks under the City Scenario by Lili Zhang, Yueheng Li, Guoping Tan, Rongbo Zhu, Hao Chen

    Published 2015-08-01
    “…In the end, we analyze and verify the efficiency of our model by theoretical deductions and simulations, and our model will be helpful to find more efficient routing algorithm and build the more trustable simulator of VANET.…”
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  8. 4868

    Machine learning-based e-commerce platform repurchase customer prediction model. by Cheng-Ju Liu, Tien-Shou Huang, Ping-Tsan Ho, Ping-Tsan Ho, Jui-Chan Huang, Ching-Tang Hsieh

    Published 2020-01-01
    “…Finally, through two sets of contrast experiments, it is proved that the algorithm selected in this paper can effectively filter the features, which simplifies the complexity of the model to a certain extent and improves the classification accuracy of machine learning. …”
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  9. 4869

    Coupled Coil Design and Magnetic Field Characteristics Analysis of Wireless Power Transfer System Based on Semi-closed Domain Coupling Resonance by ZHOU Xiwei, YANG Zewang, BAI Yehong, SHANG Xinjuan

    Published 2021-01-01
    “…In this paper, under the semi-closed nonlinear coupling state with radial, angular and radial-angle offsets, a 3D model of coupling coil is established for wireless power transmission system, and a new genetic algorithm is used to determine the parameters of the coupling coil. …”
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  10. 4870

    A Federated Learning Model for Detecting Cyberattacks in Internet of Medical Things Networks by Abdallah Ghourabi, Adel Alkhalil

    Published 2025-01-01
    “…The XGBoost models are further optimized using a Bayesian method and integrated with an aggregation algorithm to construct an adaptive global model. …”
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  11. 4871
  12. 4872

    Accelerated Transfer Learning for Cooperative Transportation Formation Change via SDPA-MAPPO (Scaled Dot Product Attention-Multi-Agent Proximal Policy Optimization) by Almira Budiyanto, Keisuke Azetsu, Nobutomo Matsunaga

    Published 2024-11-01
    “…When transfer learning is combined with fast computation, the efficiency of edge-level re-learning is improved. This paper proposes a formation change algorithm that allows easy and fast multi-robot knowledge transfer using SDPA combined with MAPPO (Multi-Agent Proximal Policy Optimization), compared to other methods. …”
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    Article
  13. 4873
  14. 4874

    Forecasting loan, deferred rate and customer segmentation in banking industry: A computational intelligence approach by Mahtab Vasheghani, Ebrahim Nazari Farokhi, Behrooz Dolatshah

    Published 2025-09-01
    “…This study proposes a novel hybrid model integrating Multi-Layer Perceptron (MLP) neural networks with Self-Adaptive Particle Swarm Optimization (PSO) and Genetic Algorithm (GA) frameworks. …”
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  15. 4875
  16. 4876

    An English Diagnostic Intelligence Evaluation Model Based on Organizational Evolutionary Information Entropy by Haiying Sang

    Published 2022-01-01
    “…In order to realize the English diagnostic intelligence evaluation, improve the English learning ability, and construct the cognitive framework of English learning, this study proposes an English diagnostic intelligence evaluation model based on the organizational evolution information entropy. …”
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  17. 4877

    A Parameter Estimation Method of DC-link Capacitor Based on Pre-charge Process of Traction Converter by LYU Gexing, ZHU Qi

    Published 2023-04-01
    “…In order to improve the reliability of the estimation, different from the traditional parameter identification algorithm based on gradient descent, the genetic algorithm is used to search for the optimal value in the range of health parameter and estimate the real parameter. …”
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  18. 4878

    Research on subway settlement prediction based on the WTD-PSR combination and GSM-SVR model by Miren Rong, Chao Feng, Yinping Pang, Hailong Wang, Ying Yuan, Wensong Zhang, Lanxin Luo

    Published 2025-05-01
    “…Furthermore, Particle Swarm Optimization (PSO), Gray Wolf Optimization (GWO), Marine Predators Algorithm (MPA), and Whale Optimization Algorithm (WOA) are introduced to optimize the SVR model, and the prediction performance is compared with that of the Long Short-Term Memory (LSTM) model. …”
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  19. 4879

    Distributed Dynamic Traffic Modeling and Implementation Oriented Different Levels of Induced Travelers by Yan Liu, Yao Yu

    Published 2015-01-01
    “…The numerical results show that the proposed model not only can improve the running efficiency of road network but also can significantly decrease the average travel time.…”
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  20. 4880

    Modeling of the Power Station Boiler Combustion Efficiency Considering Multiple Work Condition with Feature Selection by TANG Zhenhao, WU Xiaoyan, CAO Shengxian

    Published 2020-04-01
    “…It is difficult for power station boiler efficiency to measure precisely A datadriven modeling method is proposed to establish the boiler combustion efficiency model, according to the machine learning theories A classification and regression trees (CART) algorithm provides correlated variables which have significant relation with the boiler combustion efficiency by data analysis Then, a KNearest Neighbor (KNN) classifies the samples to distinguish the data from different work conditions Based on the classified data, a least square support vector machine (LSSVM) optimized by differential evolution (DE) algorithm is proposed to establish a datadriven model (DDMMF) The parameters of LSSVM are optimized dynamically by DE to improve the model accuracy Finally, the prediction model is corrected dynamically for further improvement of the prediction accuracy The experimental results based on actual production data illustrate that the proposed approach can predict the boiler combustion efficiency accurately, which meets the requirements of boiler control and optimization…”
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