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Showing 1,281 - 1,300 results of 7,292 for search '(( improved model optimization algorithm ) OR ( improved post optimization algorithm ))', query time: 0.41s Refine Results
  1. 1281

    A novel approach to node coverage enhancement in wireless sensor networks using walrus optimization algorithm by V. Saravanan, Indhumathi G, Ramya Palaniappan, Narayanasamy P, M. Hema Kumar, K. Sreekanth, Navaneethan S

    Published 2024-12-01
    “…This research introduces the Walrus Optimization Algorithm for Node Coverage Enhancement in WSNs, called the WaOA-NCEWSN technique. …”
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    Article
  2. 1282
  3. 1283

    A New Approach to Selecting Optimal Parameters for the Sliding Mode Algorithm on an Automotive Suspension System by Tuan Anh Nguyen

    Published 2023-01-01
    “…Besides, the nonlinear system’s SM (sliding mode) control algorithm is used to control the system. The SM algorithm’s parameters are optimally selected using the multiple loop algorithm. …”
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    Article
  4. 1284

    Enhanced skill optimization algorithm: Solution to the stochastic reactive power dispatch framework with optimal inclusion of renewable resources using large‐scale network by Noor Habib Khan, Yong Wang, Raheela Jamal, Sheeraz Iqbal, Mohamed Ebeed, Yazeed Yasin Ghadi, Z. M. S. Elbarbary

    Published 2024-12-01
    “…To avoid stagnation problems in skilled optimization algorithm (SOA), three strategies such as fitness‐distance balance selection, mutation, and gorilla troops‐based approaches are utilized to improve overall strength of SOA. …”
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    Article
  5. 1285

    Adaptive Reconfigurable Learning Algorithm for Robust Optimal Longitudinal Motion Control of Unmanned Aerial Vehicles by Omer Saleem, Aliha Tanveer, Jamshed Iqbal

    Published 2025-03-01
    “…The proposed algorithm is formulated to track the optimal trajectory yielded by the baseline Linear Quadratic Integral (LQI) controller. …”
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    Article
  6. 1286

    Optimization of Relay Node Deployment in Wireless Sensor Communication Networks Based on IGA-RNDP Algorithm by Shubo Xu, Cheng Zhong

    Published 2025-01-01
    “…To achieve reasonable deployment of relay nodes, a relay node deployment algorithm on the basis of improved genetic algorithm is proposed. …”
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    Article
  7. 1287

    5G-Practical Byzantine Fault Tolerance: An Improved PBFT Consensus Algorithm for the 5G Network by Xin Liu, Xing Fan, Baoning Niu, Xianrong Zheng

    Published 2025-03-01
    “…With the development of 5G network technology, its features of high bandwidth, low latency, and high reliability provide a new approach for consensus algorithm optimization. To take advantage of the features of the 5G network, this paper proposes 5G-PBFT, which is an improved practical Byzantine fault-tolerant consensus algorithm with three ways to improve PBFT. …”
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    Article
  8. 1288

    Surface Defect Detection for Small Samples of Particleboard Based on Improved Proximal Policy Optimization by Haifei Xia, Haiyan Zhou, Mingao Zhang, Qingyi Zhang, Chenlong Fan, Yutu Yang, Shuang Xi, Ying Liu

    Published 2025-04-01
    “…On the particleboard defect dataset with limited images, PPOBoardNet achieves a mean average precision (mAP) of 79.0%, representing a 5.3% performance improvement over the YOLO series of optimal detection models. …”
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    Article
  9. 1289

    Management of large energy storage power plants: optimization of charging and discharging with cuckoo search algorithm by Behnam Motalebinejad, Majid Hosseina, Mojtaba Vahedi, Mahmoud Samiei Moghaddam

    Published 2024-03-01
    “…This algorithm has the capability to find global optimal solutions and can significantly improve the efficiency and profitability of large-scale energy storage facilities. …”
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    Article
  10. 1290
  11. 1291

    An Improved Extreme Learning Machine (ELM) Algorithm for Intent Recognition of Transfemoral Amputees With Powered Knee Prosthesis by Yao Zhang, Xu Wang, Haohua Xiu, Wei Chen, Yongxin Ma, Guowu Wei, Lei Ren, Luquan Ren

    Published 2024-01-01
    “…Additionally, a hybrid grey wolf optimization and slime mould algorithm (GWO-SMA) is proposed to optimize the hidden layer bias of the improved ELM classifier. …”
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    Article
  12. 1292

    Approximated Optimal Solution for Economic Manufacturing Quantity Model by Jinyuan Liu, Pengfei Jiang, Shr-Shiung Hu, Gino K. Yang

    Published 2025-06-01
    “…This study investigates the use of the bisection algorithm in inventory models to obtain an approximated optimal solution for the economic manufacturing quantity (EMQ) problem under imperfect production conditions. …”
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    Article
  13. 1293

    Strategic scheduling of the electric vehicle-based microgrids under the enhanced particle swarm optimization algorithm by Saeed Abdollahi Khou, Javad olamaei, Mohammad Hassan Hosseini

    Published 2024-12-01
    “…However, the persistent problem of PSOAs (particle swarm optimization algorithms) being affected by local optima emphasizes the need for more improvements to these algorithms. …”
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    Article
  14. 1294

    Modification of the WaldBoost algorithm to improve the efficiency of solving pattern recognition problems in real-time by A. N. Chesalin, S. Ya. Grodzenskiy, M. Yu. Nilov, A. N. Agafonov

    Published 2019-10-01
    “…The efficiency of the proposed algorithm is shown by specific examples. The results are confirmed by statistical modeling on several data sets. …”
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    Article
  15. 1295

    Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

    Published 2022-08-01
    “…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
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    Article
  16. 1296

    Large-scale post-disaster user distributed coverage optimization based on multi-agent reinforcement learning by Wenjun XU, Silei WU, Fengyu WANG, Lan LIN, Guojun LI, Zhi ZHANG

    Published 2022-08-01
    “…In order to quickly restore emergency communication services for large-scale post-disaster users, a distributed intellicise coverage optimization architecture based on multi-agent reinforcement learning (RL) was proposed, which could address the significant differences and dynamics of communication services caused by a large number of access users, and the difficulty of expansion caused by centralized algorithms.Specifically, a distributed k-sums clustering algorithm considering service differences of users was designed in the network characterization layer, which could make each unmanned aerial vehicle base station (UAV-BS) adjust the local networking natively and simply, and obtain states of cluster center for multi-agent RL.In the trajectory control layer, multi-agent soft actor critic (MASAC) with distributed-training-distributed-execution structure was designed for UAV-BS to control trajectory as intelligent nodes.Furthermore, ensemble learning and curriculum learning were integrated to improve the stability and convergence speed of training process.The simulation results show that the proposed distributed k-sums algorithm is superior to the k-means in terms of average load efficiency and clustering balance, and MASAC based trajectory control algorithm can effectively reduce communication interruptions and improve the spectrum efficiency, which outperforms the existing RL algorithms.…”
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    Article
  17. 1297

    Hierarchical Swarm Model: A New Approach to Optimization by Hanning Chen, Yunlong Zhu, Kunyuan Hu, Xiaoxian He

    Published 2010-01-01
    “…This proposed model is intended to suggest ways that the performance of HSO-based algorithms on complex optimization problems can be significantly improved. …”
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    Article
  18. 1298

    The machine learning algorithm based on decision tree optimization for pattern recognition in track and field sports. by Guomei Cui, Chuanjun Wang

    Published 2025-01-01
    “…Specifically, by introducing adaptive feature selection and ensemble learning methods, the decision tree algorithm effectively improves the recognition ability of the model for different athletes and sports states, thus reducing the over-fitting phenomenon and improving the generalization ability. …”
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    Article
  19. 1299

    Optimization of the Hybrid Movie Recommendation System Based on Weighted Classification and User Collaborative Filtering Algorithm by Zhenning Yuan, Jong Han Lee, Sai Zhang

    Published 2021-01-01
    “…Aiming at the problem that the single model of the traditional recommendation system cannot accurately capture user preferences, this paper proposes a hybrid movie recommendation system and optimization method based on weighted classification and user collaborative filtering algorithm. …”
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    Article
  20. 1300

    Optimizing an LSTM Self-Attention Architecture for Portuguese Sentiment Analysis Using a Genetic Algorithm by Daniel Parada, Alexandre Branco, Marcos Silva, Fábio Mendonça, Sheikh Mostafa, Fernando Morgado-Dias

    Published 2025-06-01
    “…To address this complexity, a discrete genetic algorithm was used to find an optimal configuration, selecting the layer types, placement of self-attention, dropout rate, and model dimensions and shape. …”
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    Article