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  1. 1521

    E-Commerce Logistics Software Package Tracking and Route Planning and Optimization System of Embedded Technology Based on the Intelligent Era by Dan Zhang, Zhiyang Jia

    Published 2024-01-01
    “…To sum up, this algorithm could effectively optimize the distribution route of logistics packages and improve the efficiency of package transportation.…”
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    Article
  2. 1522

    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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    Article
  3. 1523

    Optimizing High-Speed Railroad Timetable with Passenger and Station Service Demands: A Case Study in the Wuhan-Guangzhou Corridor by Jin Wang, Leishan Zhou, Yixiang Yue, Jinjin Tang, Zixi Bai

    Published 2018-01-01
    “…The results show that the proposed model and algorithm can quickly reduce the defined cost function by 38.2% and improve the average travel speed by 10.7 km/h, which indicates that our proposed model and algorithm can effectively improve the quality of a constructed train timetable and the travel efficiency for passengers.…”
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    Article
  4. 1524

    Prediction of dam deformation using adaptive noise CEEMDAN and BiGRU time series modeling by WANG Zixuan, OU Bin, CHEN Dehui, YANG Shiyong, ZHAO Dingzhu, FU Shuyan

    Published 2025-07-01
    “…High-frequency modal components undergo secondary decomposition using variational mode decomposition (VMD) to extract the optimal intrinsic mode function. Finally, an improved symbiotic biological search algorithm combined with a Bidirectional Gated Recurrent Unit (BiGRU) is used to accurately predict dam deformation.…”
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    Article
  5. 1525

    Optimizing microgrid performance a multi-objective strategy for integrated energy management with hybrid sources and demand response by Mohsen Moosavi, Javad Olamaei, Hossein Mohmmadnezhad Shourkaei

    Published 2025-05-01
    “…When compared to leading optimization algorithms, the proposed approach showed better performance. …”
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    Article
  6. 1526

    Research on the optimal scheduling of a multi-storage combined integrated energy system based on an energy supply grading strategy by Na Zhang, Feng You, Bingqian Hu, Jingyu Li, Guangchen Liu

    Published 2025-02-01
    “…Next, considering the system operational cost and carbon emission cost as the optimization goal, a comprehensive energy optimization scheduling model of multi-storage combined hierarchical energy supply is constructed. …”
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    Article
  7. 1527

    Co-Optimization Operation of Distribution Network-Containing Shared Energy Storage Multi-Microgrids Based on Multi-Body Game by Hao Wu, Ge Cao, Rong Jia, Yan Liang

    Published 2025-01-01
    “…Finally, based on the power interaction of microgrids to measure their contributions, an improved Shapley value cost allocation method is proposed, effectively achieving a balanced distribution of benefits among the distribution network, shared energy storage, and multi-microgrids, thereby improving overall operational revenue. …”
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    Article
  8. 1528

    Next generation network resource allocation method based on cooperative game and decision-making in advance by RAO Xiang, ZHANG Shun-yi, SUN Yan-fei, DING Wen-tao

    Published 2009-01-01
    “…It’s an important way to guarantee QoS for the next generation network(NGN) with diverse services by allo-cating resources reasonably and optimizing the efficiency of whole network according to diverse service styles.A net-work resource allocating method based on co-operative game theory for NGN was proposed and analyzed,and it had a weakness which brought about overgreat system costing.In order to overcome this weakness,an idea about deci-sion-making in advance was added,and an improved resource allocation algorithm was proposed,which could guarantee the efficiency of whole network best and reduce the system costing.Simulation results of this method show its validity.…”
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    Article
  9. 1529

    Enhancing microgrid forecasting accuracy with a TCNN-TLS framework: A novel approach to mitigating uncertainty in renewable energy and load predictions by Md. Omer Faruque, Md. Majharul Islam, Md Jakaria Talukder, Arif Mia, Shahriar Tasnim, Md. Alamgir Hossain, S.M. Muyeen

    Published 2025-09-01
    “…The employed settings contain a temporal convolutional neural network (TCNN) optimized with a pelican optimization algorithm (POA) to enhance its hyper-parameter selection. …”
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    Article
  10. 1530

    Next generation network resource allocation method based on cooperative game and decision-making in advance by RAO Xiang, ZHANG Shun-yi, SUN Yan-fei, DING Wen-tao

    Published 2009-01-01
    “…It’s an important way to guarantee QoS for the next generation network(NGN) with diverse services by allo-cating resources reasonably and optimizing the efficiency of whole network according to diverse service styles.A net-work resource allocating method based on co-operative game theory for NGN was proposed and analyzed,and it had a weakness which brought about overgreat system costing.In order to overcome this weakness,an idea about deci-sion-making in advance was added,and an improved resource allocation algorithm was proposed,which could guarantee the efficiency of whole network best and reduce the system costing.Simulation results of this method show its validity.…”
    Get full text
    Article
  11. 1531

    Energy Storage Configuration Optimization of a Wind–Solar–Thermal Complementary Energy System, Considering Source-Load Uncertainty by Guangxiu Yu, Ping Zhou, Zhenzhong Zhao, Yiheng Liang, Weijun Wang

    Published 2025-07-01
    “…Firstly, a deterministic bi-level model is constructed: the upper level aims to minimize the comprehensive cost of the system to determine the energy storage capacity and power, and the lower level aims to minimize the system operation cost to solve the optimal scheduling scheme. …”
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    Article
  12. 1532

    Improving agricultural management zoning involving Sentinel-2 timeseries, crop’s phenology stages and proximal soil sensing data by Larissa Torney, Cornelia Weltzien, Martin Herold, Sebastian Vogel, Sebastian Voß

    Published 2025-07-01
    “…Our hypothesis that the clustering based on soil and phenology separated vegetation data would improve the management zones was refuted. The vegetation cluster, which was based on the entire Sentinel-2 timeseries, exhibited optimal performance, for one field in Groß Kreutz, Germany. …”
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    Article
  13. 1533

    Modular Coordination of Vehicle Routing and Bin Packing Problems in Last Mile Logistics by Nikica Perić, Anđelko Kolak, Vinko Lešić

    Published 2025-05-01
    “…<i>Background</i>: Logistics and transport, core of many business processes, are continuously optimized to improve efficiency and market competitiveness. …”
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    Article
  14. 1534

    Network Optimization of Fresh Products Cold Chain Considering Supply Disruption and Demand Fluctuation Under the Dual-Carbon Policy by Haojie Ran, Dichen He, Huajun Tang

    Published 2025-05-01
    “…The research results provide valuable decision-making support for fresh cold chain enterprises to develop resilient and low-carbon network optimization strategies for cost reduction, efficiency improvement, and sustainable development.…”
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    Article
  15. 1535

    Risk-managed economic dispatch in hybrid hydrothermal-wind-solar systems: a novel multi-objective optimization approach by Zhe Wang, Tao Sun, Na Liu

    Published 2025-08-01
    “…The model integrates spinning reserve (SR) constraints and a synchronous peak shaving strategy to enhance system stability and cost efficiency. A Multi-Objective Artificial Rabbits Optimization (MOARO) algorithm, incorporating Pareto criteria and fuzzy theory, is applied to optimize dispatch decisions while balancing cost and risk. …”
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    Article
  16. 1536

    Soft-sensor modeling of silicon content in hot metal based on sparse robust LS-SVR and multi-objective optimization by GUO Dong-wei, ZHOU Ping

    Published 2016-09-01
    “…Last, the multi-objective evaluation index that synthesizes the modeling residue and the estimated trend was&nbsp;presented to compensate for the deficiency of the single root mean square error (RMSE) index. Based on those, an on-line soft sensor model of hot metal[Si] with the optimal parameters was obtained by using the multi-objective genetic algorithm (NSGA-Ⅱ) with the non-dominated sort and elitist strategy. …”
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    Article
  17. 1537

    Layout optimization of multi-level cold chain storage facilities in agricultural producing areas considering type and capacity constraints. by Qian Huang, Guijun Zheng, Shuangli Pan, Huiyu Liao, Zehua Jiang

    Published 2025-01-01
    “…Based on the above considerations, with the aim of minimizing the total daily cost, an optimization model for the layout of multi-level cold chain storage facilities is established to determine the number, location, type and capacity of cold chain storage facilities at the same time. …”
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    Article
  18. 1538

    Meta-RHDC: Meta Reinforcement Learning Driven Hybrid Lyrebird Falcon Optimization for Dynamic Load Balancing in Cloud Computing by Mallu Shiva Rama Krishna, D. Khasim Vali

    Published 2025-01-01
    “…By integrating reinforcement learning with advanced optimization techniques, Meta-RHDC significantly improves task scheduling and load balancing compared to existing methods such as Load Optimization Algorithm (LOA), Reinforcement Learning (RL), and Falcon Optimization Algorithm (FOA). …”
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    Article
  19. 1539

    Enhancing Streamflow Prediction Accuracy: A Comprehensive Analysis of Hybrid Neural Network Models with Runge–Kutta with Aquila Optimizer by Rana Muhammad Adnan, Wang Mo, Ahmed A. Ewees, Salim Heddam, Ozgur Kisi, Mohammad Zounemat-Kermani

    Published 2024-11-01
    “…Abstract This study investigates the efficacy of hybrid artificial neural network (ANN) methods, incorporating metaheuristic algorithms such as particle swarm optimization (PSO), genetic algorithm (GA), gray wolf optimizer (GWO), Aquila optimizer (AO), Runge–Kutta (RUN), and the novel ANN-based Runge–Kutta with Aquila optimizer (LSTM-RUNAO). …”
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    Article
  20. 1540