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  1. 4641

    Integrated Systemic Modeling of Production Scheduling, Maintenance, and Quality Control in Closed-Loop Supply Chains by Javad Rahim, Ali Morovati Sharifabadi, Davood Andalib Ardakani

    Published 2025-03-01
    “…A Genetic Algorithm (GA) was utilized to optimize decision variables, including sample size, sampling intervals, control limits, and maintenance schedules, ensuring robust solutions under real-world constraints. …”
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  2. 4642

    Causation Analysis of Marine Traffic Accidents Using Deep Learning Approaches: A Case Study from China’s Coasts by Zelin Zhao, Xingyu Liu, Lin Feng, Manel Grifoll, Hongxiang Feng

    Published 2025-04-01
    “…In response to the increasing frequency of maritime traffic accidents along China’s coast, this study develops an accident-cause analysis framework that integrates an optimized Bidirectional Encoder Representations from Transformers (BERT) with a Bidirectional Long Short-Term Memory network (BiLSTM), combined with the Apriori association rule algorithm. …”
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  3. 4643

    Electricity pinch analysis method for flexibility supply-demand matching in power systems by Yaling Mao, Tiejiang Yuan, Xueqin Tian, Yue Teng

    Published 2025-10-01
    “…First, the net-load profile is decomposed by successive variational mode decomposition (SVMD) optimized with the Red-billed Blue Magpie Optimization (RBMO) algorithm to construct a flexibility demand model. …”
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  4. 4644

    Research on Adaptive Identification Technology for Rolling Bearing Performance Degradation Based on Vibration–Temperature Fusion by Zhenghui Li, Lixia Ying, Liwei Zhan, Shi Zhuo, Hui Li, Xiaofeng Bai

    Published 2025-07-01
    “…Finally, a dual-criteria adaptive bottom-up merging algorithm (DC-ABUM) was proposed, which achieves bearing life-stage identification through error threshold constraints and the adaptive optimization of segmentation quantities. …”
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  5. 4645

    Improvement of Network Traffic Prediction in Beyond 5G Network using Sparse Decomposition and BiLSTM Neural Network by Rihab Abdullah Jaber Al Hamadani, Mahdi Mosleh, Ali Hashim Abbas Al-Sallami, Rasool Sadeghi

    Published 2025-04-01
    “…Next, sparse feature extraction is performed using Discrete Wavelet Transform (DWT), and a sparse matrix is constructed. A Genetic Algorithm (GA) is used to optimize the sparse matrix, which effectively selects the most significant features for prediction. …”
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  6. 4646

    Support Vector Machine – Recursive Feature Elimination for Feature Selection on Multi-omics Lung Cancer Data by Nuraina Syaza Azman, Azurah A Samah, Ji Tong Lin, Hairudin Abdul Majid, Zuraini Ali Shah, Nies Hui Wen, Chan Weng Howe

    Published 2023-04-01
    “…Additionally, 1000 and 4000 are the two most optimal feature subsets selected by the SVM-RFE algorithm. …”
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    Article
  7. 4647

    Transformer Fault Diagnosis Based on Knowledge Distillation and Residual Convolutional Neural Networks by Haikun Shang, Yanlei Wei, Shen Zhang

    Published 2025-06-01
    “…Subsequently, the Sparrow Optimization Algorithm (SSA) is applied to optimize the hyperparameters of the ResNet50 model, which is trained on DGA data as the teacher model. …”
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  8. 4648

    Fairness-Aware Utility Maximization for Multi-UAV-Aided Terrestrial Networks by Nishant Gupta, Satyam Agarwal, Aymen Fakhreddine

    Published 2024-01-01
    “…In the first stage, we propose a heuristic solution by using the clustering algorithm to determine the initial ABS locations and user scheduling while ignoring the co-channel interference. …”
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  9. 4649

    A Framework for Synergy Measurement Between Transportation and Production–Living–Ecological Space Using Volume-to-Capacity Ratio, Accessibility, and Coordination by Xiaoyi Ma, Mingmin Liu, Jingru Huang, Ruihua Hu, Hongjie He

    Published 2025-07-01
    “…By introducing an improved accessibility evaluation model and developing a coordination measurement algorithm, a three-dimensional evaluation mechanism covering development potential assessment, service efficiency diagnosis, and resource allocation optimization is established. …”
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    Article
  10. 4650

    A Capacitated Vehicle Routing Model for Distribution and Repair with a Service Center by Irma-Delia Rojas-Cuevas, Elias Olivares-Benitez, Alfredo S. Ramos, Samuel Nucamendi-Guillén

    Published 2025-02-01
    “…Additionally, a Variable Neighborhood Search (VNS) algorithm was implemented and compared with AMPL-Gurobi. …”
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    Article
  11. 4651

    Charging Station Management Strategy for Returns Maximization via Improved TD3 Deep Reinforcement Learning by Hengjie Li, Jianghao Zhu, Yun Zhou, Qi Feng, Donghan Feng

    Published 2022-01-01
    “…Also, we use marginalised importance sampling to calculate the Q-return function for TD3, which ensures that the constructed strategies are more likely to learn high-value experiences while having higher robustness. It is shown in numerical experiments that the charging station management strategy (CSMS) based on the modified TD3 obtains the fastest convergence speed and the highest robustness and achieves the largest operational returns compared to the CSMS constructed using deep deterministic policy gradient (DDPG), actor-critic using Kronecker-factored trust region (ACKTR), trust region policy optimization (TRPO), proximal policy optimization (PPO), soft actor-critic (SAC), and the original TD3.…”
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  12. 4652

    Myocarditis Diagnosis Using Semi-Supervised Generative Adversarial Network and Differential Evolution by Haifeng Gui, Na Zhang

    Published 2024-09-01
    “…To minimize reliance on hyperparameters, the Random Key method is employed, optimized using the DE algorithm. The efficacy of the model is demonstrated on the Z-Alizadeh Sani myocarditis dataset, with further validation achieved through experiments on the EMIDEC dataset, assessing transfer learning (TL) effects. …”
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  13. 4653

    Enhancing Ability Estimation with Time-Sensitive IRT Models in Computerized Adaptive Testing by Ahmet Hakan İnce, Serkan Özbay

    Published 2025-06-01
    “…Seven models were evaluated, including standard 1PL-IRT and six response-time-adjusted variants: TP-IRT, STP-IRT, TWD-IRT, NRT-IRT, DTA-IRT, and ART-IRT. Three optimization techniques—Maximum Likelihood Estimation (MLE), full parameter optimization, and K-fold Cross-Validation (CV)—were employed to assess model performance. …”
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  14. 4654

    Using 'sentinel' plants to improve early detection of invasive plant pathogens. by Francesca A Lovell-Read, Stephen Parnell, Nik J Cunniffe, Robin N Thompson

    Published 2023-02-01
    “…Using Xylella fastidiosa infection in Olea europaea (European olive) as a current high profile case study, for which Catharanthus roseus (Madagascan periwinkle) is a candidate sentinel host, we apply a Bayesian optimisation algorithm to determine the optimal number of sentinel hosts to introduce for a given sampling effort, as well as the optimal division of limited surveillance resources between crop and sentinel plants. …”
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  15. 4655

    Genome-wide comparative analysis of variability and population structure between autochthonous Turkish chicken breeds and commercial hybrid lines by Eymen Demir, Bahar Argun Karsli, Demir Özdemir, Umit Bilginer, Huriye Doğru, Sarp Kaya, Veli Atmaca, Nimet Tufan, Ebru Demir, Taki Karsli

    Published 2025-07-01
    “…A total of 94,208 bi-allelic SNPs were common between DNZ and GRZ, while 33,284 SNPs were retained among all populations after the quality filtering process. …”
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  16. 4656

    Selection of methods and tools of voltage unbalance reduction within the Eastern part of Siberian integrated power system by V. V. Dikovich, E. M. Katz, O. S. Stremilova

    Published 2017-12-01
    “…The conducted researches give an opportunity to choose technical tools and their installation sites to reduce voltage unbalance in the optimal way, that will help to increase operational reliability of consumers and the electric power system as a whole.…”
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  17. 4657

    Deep learning assisted analysis of biomarker changes in refractory neovascular AMD after switch to faricimab by Michael Hafner, Franziska Eckardt, Jakob Siedlecki, Benedikt Schworm, Tina R. Herold, Ben Asani, Siegfried G. Priglinger, Johannes B. Schiefelbein

    Published 2025-04-01
    “…Faricimab demonstrated significant and sustained anatomical improvements, allowing for extended treatment intervals while maintaining disease stability. Future research should focus on refining AI models to improve predictive accuracy and assessing long-term outcomes to further optimize disease management. …”
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  18. 4658

    Perceptual-Preference-Based Touring Routes in Xishu Gardens Using Panoramic Digital-Twin Modeling by Xueqian Gong, Zhanyuan Zhu, Li Guo, Yong Zhong, Deshun Zhang, Jing Li, Manqin Yao, Wei Yong, Mengjia Li, Yujie Huang

    Published 2025-04-01
    “…Xishu Gardens, an exemplary narrative of classical Chinese gardens, faces challenges in preserving its commemorative spatial structures while accommodating modern visitors’ needs. While trajectory analysis is critical, existing studies struggle to interpret multi-dimensional perception-preference data owing to spatiotemporal mismatches in multi-source datasets. …”
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  19. 4659

    Resource allocation for coexistence of eMBB and bursty URLLC based on queueing with preemption by Wei Guo, Kai Liang, Yuewen Song, Xiaoli Chu, Gan Zheng, Kai-Kit Wong

    Published 2025-05-01
    “…Based on this analysis, we formulate a mixed-integer nonlinear programming problem to minimize the average delay of URLLC packets while satisfying the average delay and throughput requirements of eMBB by jointly optimizing the eMBB subcarrier allocation, the URLLC subcarrier scheduling and the computing resource allocation. …”
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  20. 4660

    Leveraging petrophysical and geological constraints for AI-driven predictions of total organic carbon (TOC) and hardness in unconventional reservoir prospects by Nandito Davy, Ammar El-Husseiny, Umair bin Waheed, Korhan Ayranci, Manzar Fawad, Mohamed Mahmoud, Nicholas B. Harris

    Published 2024-12-01
    “…Petrophysical constraints were derived from triple combo well logs (gamma ray, bulk density, neutron porosity), while geological constraints included stratigraphic data or spatial distance between training and target wells—petrophysical constraints most improved predictions, while stratigraphic and spatial constraints had progressively less impact. …”
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    Article