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  1. 601

    An optimized method for short-term load forecasting based on feature fusion and ConvLSTM-3D neural network by Xiaofeng Yang, Shousheng Zhao, Kangyi Li, Wenjin Chen, Si Zhang, Jingwei Chen

    Published 2025-01-01
    “…As renewable energy continues to penetrate modern power systems, accurate short-term load forecasting is crucial for optimizing power generation resource allocation and reducing operational costs. …”
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    Article
  2. 602

    Recent advancements in stereolithography (SLA) and their optimization of process parameters for sustainable manufacturing by Asmaul Husna, Salahuddin Ashrafi, ANM Amanullah Tomal, Noshin Tasnim Tuli, Adib Bin Rashid

    Published 2024-12-01
    “…Furthermore, the paper discusses the application of optimization methods like Genetic Algorithms and Artificial Neural Networks (ANN) to analyze, refine, and determine the optimal processing parameters for stereolithography. …”
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    Article
  3. 603

    Advancing smart aquaculture: Cost-efficient strategies for climbing perch cultivation using AI-based models by Kosit Sriputhorn, Achara Jutagate, Surasak Matitopanum, Rungwasun Kraiklang, Rapeepan Pitakaso, Chakat Chueadee, Sarayut Gonwirat

    Published 2025-12-01
    “…This study introduces a hybrid AI-based optimization framework to enhance climbing perch aquaculture in smart farming systems, targeting improvements in both productivity and cost-efficiency. …”
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    Article
  4. 604

    Web services composition algorithm based on the location of backup service and probabilistic QoS model by Hua WEN

    Published 2016-10-01
    “…For the service selection problem, an improved multiple objective optimization(MOO)algorithm was adopted to calculate the feasible solution set using clustering and QoS model. …”
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    Article
  5. 605

    Web services composition algorithm based on the location of backup service and probabilistic QoS model by Hua WEN

    Published 2016-10-01
    “…For the service selection problem, an improved multiple objective optimization(MOO)algorithm was adopted to calculate the feasible solution set using clustering and QoS model. …”
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    Article
  6. 606
  7. 607

    Optimizing Container Repositioning Using a Sequential Insertion Algorithm for Pickup-Delivery Routing in Export-Import Operations by Ary Arvianto, Dihan Chofifah Cahyani, Dhimas Wachid Nur Saputra

    Published 2025-04-01
    “…The increasing number of empty containers significantly causes to traffic congestion and rising operational costs, thereby necessitating the development of an optimized routing model to enhance fleet utilization and minimize transportation expenses. …”
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    Article
  8. 608

    Multi-UAV Trajectory Optimization Under Dynamic Threats: An Enhanced GWO Algorithm Integrating a Priori and Real-Time Data by Zihan Zhou, Yanhong Guo, Yitao Wang, Jingfan Lyu, Haoran Gong, Xin Ye, Yachao Li

    Published 2025-06-01
    “…Our research integrates a priori knowledge of threat zone locations, speeds, and directions with real-time data on the UAVs position relative to the threat zones to effectively manage dynamic threat zones, allowing UAVs to dynamically decide whether to navigate around or through these zones, thus significantly reducing trajectory costs. To further improve search efficiency and solution quality, strategies such as greedy initialization and K-means clustering are incorporated, enhancing the algorithms multi-objective optimization capabilities. …”
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    Article
  9. 609
  10. 610

    A Model Predictive Control to Improve Grid Resilience by Joseph Young, David G. Wilson, Wayne Weaver, Rush D. Robinett

    Published 2025-04-01
    “…Previous work on MPCs has focused on narrowly targeted control applications such as improving electric vehicle (EV) charging infrastructure or reducing the cost of integrating Energy Storage Systems (ESSs) into the grid. …”
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    Article
  11. 611

    Robust Improvement Strategy for Power Grid Hosting Capacity with Integration of High Proportion of Renewable Energy by Yangqing DAN, Lei WANG, Weimin ZHENG, Jiahui WU, Chenxuan WANG, Gaowang YU

    Published 2023-09-01
    “…And then, based on the two-stage robust optimization theory, a strategy model for improving the hosting capacity of the power grid is constructed, and the column and constraint generation (C&CG) algorithm is used to solve the model. …”
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    Article
  12. 612

    Optimizing Multi-Echelon Delivery Routes for Perishable Goods with Time Constraints by Manqiong Sun, Yang Xu, Feng Xiao, Hao Ji, Bing Su, Fei Bu

    Published 2024-12-01
    “…The results demonstrate that the initial solutions obtained through the k-medoids clustering algorithm based on spatio-temporal distance improved the overall cost optimization by 1.85% and 4.74% compared to the other two algorithms. …”
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    Article
  13. 613

    Advanced AI approaches for the modeling and optimization of microgrid energy systems by Mohammed Amine Hoummadi, Badre Bossoufi, Mohammed Karim, Ahmed Althobaiti, Thamer A. H. Alghamdi, Mohammed Alenezi

    Published 2025-04-01
    “…Three AI techniques, Genetic Algorithm (GA), Artificial Bee Colony (ABC), and Ant Colony Optimization (ACO), are employed to optimize the optimal composition of energy sources based on solar energy and wind energy, battery storage, and load profiles. …”
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    Article
  14. 614

    TBESO-BP: an improved regression model for predicting subclinical mastitis by Kexin Han, Yongqiang Dai, Huan Liu, Junjie Hu, Leilei Liu, Zhihui Wang, Liping Wei

    Published 2025-04-01
    “…The TBESO algorithm notably enhances the efficacy of the BP neural network in regression prediction, ensuring elevated computational efficiency and practicality post-improvement.…”
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    Article
  15. 615

    Optimized customer churn prediction using tabular generative adversarial network (GAN)-based hybrid sampling method and cost-sensitive learning by I Nyoman Mahayasa Adiputra, Paweena Wanchai, Pei-Chun Lin

    Published 2025-06-01
    “…However, these methods have not performed well with classical machine learning algorithms. Methods To optimize the performance of classical machine learning on customer churn prediction tasks, this study introduces an extension framework called CostLearnGAN, a tabular generative adversarial network (GAN)-hybrid sampling method, and cost-sensitive Learning. …”
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    Article
  16. 616

    Metaheuristic Optimization of Wind Turbine Airfoils with Maximum-Thickness and Angle-of-Attack Constraints by Jinane Radi, Jesús Enrique Sierra-García, Matilde Santos, Carlos Armenta-Déu, Abdelouahed Djebli

    Published 2024-12-01
    “…The drag and lift coefficients are estimated, and a metaheuristic optimization technique, genetic algorithm, is applied to maximize the glide ratio while reducing the difference from the desired design parameters. …”
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    Article
  17. 617
  18. 618

    A Novel Six-Dimensional Chimp Optimization Algorithm—Deep Reinforcement Learning-Based Optimization Scheme for Reconfigurable Intelligent Surface-Assisted Energy Harvesting in Batt... by Mehrdad Shoeibi, Anita Ershadi Oskouei, Masoud Kaveh

    Published 2024-12-01
    “…Compared to benchmark algorithms, our approach achieves higher gains in harvested power, an improvement in the data rate at a transmit power of 20 dBm, and a significantly lower root mean square error (RMSE) of 0.13 compared to 3.34 for standard RL and 6.91 for the DNN, indicating more precise optimization of RIS phase shifts.…”
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  19. 619

    Smart building energy management with renewables and storage systems using a modified weighted mean of vectors algorithm by Mohamed Ebeed, Sabreen hassan, Salah Kamel, Loai Nasrat, Ali Wagdy Mohamed, Abdel-Raheem Youssef

    Published 2025-02-01
    “…Firstly, it employs the Elite Centroid Quasi-Oppositional Base Learning (ECQOBL) approach to improve the exploitation capabilities of conventional algorithms. …”
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  20. 620

    Adaptive Bayesian optimization for proportional derivative control in double-acting piston pump ventilators by Cong Toai Truong, Trung Dat Phan, Van Tu Duong, Huy Hung Nguyen, Thanh Truong Nguyen, Tan Tien Nguyen

    Published 2025-07-01
    “…Experimental results demonstrate that the proposed algorithm significantly improves system performance, reducing both tidal volume error and control cost compared to manual tuning. …”
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    Article