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  1. 401

    Human resource management model based on multi-objective differential evolution and multi-skill scheduling by Yanxia Dong, Tiantian Lu

    Published 2025-12-01
    “…This study proposes an innovative human resource management model that integrates multi-objective differential evolution algorithm and learning curve model, and adopts a multidimensional chromosome encoding scheme for multi skill scheduling. …”
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    Article
  2. 402

    Enhancing e-learning through AI: advanced techniques for optimizing student performance by Rund Mahafdah, Seifeddine Bouallegue, Ridha Bouallegue

    Published 2024-12-01
    “…This study offers a thorough examination of how AI can be utilized to enhance e-learning results by employing advanced predictive methods and performance optimization strategies. The main goals consist of creating an AI-based framework to monitor and analyze student interactions, evaluating the influence of online learning platforms on student understanding using advanced algorithms, and determining the most efficient methods for blended learning systems. …”
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  3. 403
  4. 404

    Estimating forest aboveground carbon sink based on landsat time series and its response to climate change by Kun Yang, Kai Luo, Jialong Zhang, Bo Qiu, Feiping Wang, Qinglin Xiao, Jun Cao, Yunrun He, Jian Yang

    Published 2025-01-01
    “…We found that (1) GA can effectively improve the estimation accuracy of RF, the R 2 can be improved by up to 34.8%, and the optimal GA-RF model R 2 is 0.83. (2) The CSI of Pinus densata in Shangri-La was 0.45–0.72 t C·hm− 2 from 1987 to 2017. (3) Precipitation has the most significant effect on CSI. …”
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    Predictive Ecological Cooperative Control of Electric Vehicles Platoon on Hilly Roads by Bingbing Li, Weichao Zhuang, Boli Chen, Hao Zhang, Sheng Yu, Jianrun Zhang, Guodong Yin

    Published 2025-03-01
    “…Unlike most existing literature that focuses on suboptimal coordination under predefined leading vehicle trajectories, this strategy employs an approach based on the combination of a long short-term memory network (LSTM) and genetic algorithm (GA) optimization (GA-LSTM) to predict the future speed of the leading vehicle. …”
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  9. 409

    Multi objective optimization and experimental investigation of the stirring performance of a novel micro actuator by Zhuowei He, Junjie Lei, Jingjing Yang, Huba Zhu

    Published 2025-05-01
    “…Subsequently, the Non-dominated Sorting Genetic Algorithm III (NSGA-III) is utilized for Multi-Objective Optimization to identify the optimal combination of structural parameters. …”
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  10. 410

    Conditional distributionally robust dispatch for integrated transmission-distribution systems via distributed optimization by Jie Li, Xiuli Wang, Zhicheng Wang, Zhenzi Song

    Published 2025-05-01
    “…This paper closes this gap by proposing a conditional distributionally robust optimization (DRO) method for ITDSs. Specifically, a novel ambiguity set is built by exploiting the dependence of the wind power forecast error on its forecast value, which differs from most of the existing ones. …”
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  11. 411

    Data-Driven Battery Remaining Life Prediction Based on ResNet with GA Optimization by Jixiang Zhou, Weijian Huang, Haiyan Dai, Chuang Wang, Yuhua Zhong

    Published 2025-05-01
    “…To this end, this paper proposes a data-driven lithium-ion battery life prediction method based on residual network (ResNet) and genetic algorithm (GA) optimization, which is designed to screen the features of the lithium-ion battery training data in order to effectively reduce the redundant features and improve the prediction performance of the model. …”
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    Article
  12. 412

    Bionic Compass Method Based on Atmospheric Polarization Optimization in Non-Ideal Clear Condition by Yuyang Li, Xia Wang, Min Zhang, Ruiqiang Li, Qiyang Sun

    Published 2024-11-01
    “…This paper proposes a bionic navigation method based on atmospheric polarization optimization to improve heading accuracy under non-ideal clear conditions. …”
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  13. 413

    Optimizing Q-Learning for Automated Cavity Filter Tuning: Leveraging PCA and Neural Networks by Aghanim Amina, Otman Oulhaj, Oukaira Aziz, Lasri Rafik

    Published 2025-01-01
    “…This paper presents a reinforcement learning-based approach to automate the tuning of a 6thorder combline bandpass filter, operating at 941 MHz, using a Q-learning algorithm. To reduce complexity, only two tuning screws are considered in the optimization. …”
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    Enhancing Port Energy Autonomy Through Hybrid Renewables and Optimized Energy Storage Management by Dimitrios Cholidis, Nikolaos Sifakis, Nikolaos Savvakis, George Tsinarakis, Avraam Kartalidis, George Arampatzis

    Published 2025-04-01
    “…The paper adopts a genetic algorithm (GA)-based optimization framework to assess four energy management scenarios that embed wind turbines (WTs), photovoltaic energy (PV), an energy storage system (ESS), and an energy management system (EMS). …”
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  18. 418

    Prediction of performance and emission features of diesel engine using alumina nanoparticles with neem oil biodiesel based on advanced ML algorithms by M. S. Aswathanrayan, N. Santhosh, Srikanth Holalu Venkataramana, Kurugundla Sunil Kumar, Sarfaraz Kamangar, Amir Ibrahim Ali Arabi, Sameer Algburi, Osamah J. Al-sareji, A. Bhowmik

    Published 2025-04-01
    “…The random forest model demonstrated the highest predictive accuracy for performance (test R2 = 0.9620, Test MAPE = 3.6795%), making it the most reliable statistical approach for predicting BSFC compared to linear regression and decision Tree models. …”
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  19. 419

    Research on a Wear Defect Detection Method for a Switch Sliding Baseplate Based on Improved Yolov5 by Qing Jiang, Ruipeng Gao, Yan Zhao, Wenzhen Yu, Zhuofan Dang, Shiyi Deng

    Published 2024-11-01
    “…The experimental results demonstrate that, in comparison with the currently prevalent mainstream target detection algorithms, the improved model can attain optimal recall rates R, mAP@0.5, and mAP@0.5:0.95. …”
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  20. 420

    Explainable Artificial Intelligence (XAI) for Flood Susceptibility Assessment in Seoul: Leveraging Evolutionary and Bayesian AutoML Optimization by Kounghoon Nam, Youngkyu Lee, Sungsu Lee, Sungyoon Kim, Shuai Zhang

    Published 2025-06-01
    “…Ten topographic and environmental conditioning factors were selected as model inputs. We first employed the Tree-based Pipeline Optimization Tool (TPOT), an evolutionary AutoML algorithm, to construct baseline ensemble models using Gradient Boosting (GB), Random Forest (RF), and XGBoost (XGB). …”
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