Showing 301 - 320 results of 1,750 for search '(improved OR improve) (root OR most) optimization algorithm', query time: 0.27s Refine Results
  1. 301

    Acute severe ulcerative colitis: using JAK-STAT inhibitors for improved clinical outcomes by Shruthi Karthikeyan, Chetan Ambastha, Kian Keyashian

    Published 2024-11-01
    “…Here we discuss methods to optimize the dosing of IFX to maximize its efficacy, while exploring recent work done on the safety and efficacy of JAK-STAT inhibitors as a salvage therapy, therefore suggesting a novel treatment algorithm to improve clinical outcomes in medically managed ASUC patients.…”
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    Article
  2. 302

    Improved Asphalt Pavement Crack Detection Model Based on Shuffle Attention and Feature Fusion by Tursun Mamat, Abdukeram Dolkun, Runchang He, Yonghui Zhang, Zulipapar Nigat, Hanchen Du

    Published 2025-01-01
    “…However, traditional methods for crack detection often suffer from low efficiency and limited accuracy, necessitating improvements in the accuracy of existing crack detection algorithms. …”
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    Article
  3. 303

    Access selection algorithm for heterogeneous wireless network based on DA optimized fuzzy neural network by Zhihong QIAN, Yinuo FENG, Jiani SUN, Xue WANG

    Published 2020-12-01
    “…To solve the access selection problem of heterogeneous wireless network, an access selection algorithm based on dragonfly algorithm (DA) optimized fuzzy neural network (FNN) was proposed, considering the user’s business type and network state.In view of the low convergence speed of the fuzzy neural network, the dragonfly algorithm was used to optimize the membership function parameters of the second and fifth layers of the fuzzy neural network, so as to obtain the initial value of membership function parameters of the fuzzy neural network.The most suitable network was selected for the users according to their preference to the network and the output score of the network under different business types.The experimental results show that dragonfly algorithm optimization can improve the convergence speed of fuzzy neural network, improve system throughput, reduce blocking rate, and reduce switching times to some extent.…”
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    Article
  4. 304

    Access selection algorithm for heterogeneous wireless network based on DA optimized fuzzy neural network by Zhihong QIAN, Yinuo FENG, Jiani SUN, Xue WANG

    Published 2020-12-01
    “…To solve the access selection problem of heterogeneous wireless network, an access selection algorithm based on dragonfly algorithm (DA) optimized fuzzy neural network (FNN) was proposed, considering the user’s business type and network state.In view of the low convergence speed of the fuzzy neural network, the dragonfly algorithm was used to optimize the membership function parameters of the second and fifth layers of the fuzzy neural network, so as to obtain the initial value of membership function parameters of the fuzzy neural network.The most suitable network was selected for the users according to their preference to the network and the output score of the network under different business types.The experimental results show that dragonfly algorithm optimization can improve the convergence speed of fuzzy neural network, improve system throughput, reduce blocking rate, and reduce switching times to some extent.…”
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    Article
  5. 305

    Study on optimization of Al6061 sphere surface roughness in diamond turning based on central composite design model and grey wolf optimizer algorithms by Le Thanh Binh, Duong Xuan Bien, Ngo Viet Hung, Chu Anh My, Hoang Nghia Duc, Nguyen Kim Hung, Bui Kim Hoa

    Published 2025-02-01
    “…This paper presents optimization results of the Al6061 surface roughness in turning ultra-precision based on the central composite design method (CCD) and the grey wolf optimization algorithm (GWO). …”
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    Article
  6. 306

    A Multi-Surrogate Assisted Multi-Tasking Optimization Algorithm for High-Dimensional Expensive Problems by Hongyu Li, Lei Chen, Jian Zhang, Muxi Li

    Published 2024-12-01
    “…Surrogate-assisted evolutionary algorithms (SAEAs) are widely used in the field of high-dimensional expensive optimization. …”
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    Article
  7. 307

    A Markov decision optimization of medical service resources for two-class patient queues in emergency departments via particle swarm optimization algorithm by Chia-Hung Wang, Rong Tian, Kun Hu, Yu-Tin Chen, Tien-Hsiung Ku

    Published 2025-01-01
    “…The particle swarm optimization algorithm was applied to determine the optimal number of servers, service rate, and number of beds. …”
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    Article
  8. 308

    An intelligence technique for route distance minimization to store and marketize the crop using computational optimization algorithms by Saikat Banerjee, Abhoy Chand Mondal

    Published 2025-08-01
    “…The algorithm aims to find the most efficient path that includes all locations in a given set without revisiting any point. …”
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    Article
  9. 309

    A Surrogate-Assisted Gray Prediction Evolution Algorithm for High-Dimensional Expensive Optimization Problems by Xiaoliang Huang, Hongbing Liu, Quan Zhou, Qinghua Su

    Published 2025-03-01
    “…In SAGPE, both the global and local surrogate model are constructed to assist the GPE search alternately. The proposed algorithm improves optimization efficiency by combining the macro-predictive ability of the even gray model in GPE for population update trends and the predictive ability of surrogate models to synergistically guide population searches in promising directions. …”
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    Article
  10. 310

    VERIFICATION OF THE PARSEC METHOD AND OPTIMIZATION OF NACA-4412, SG-6043 USING GENETIC ALGORITHM IN MATLAB by Raheem Alhamdawee, M. Manzoor Hussain

    Published 2025-02-01
    “…The study also includes the improvement of the aerodynamic design of both airfoils through the use of a genetic algorithm which is coded and run in MATLAB, with the PARSEC parameters used as the base for optimization. …”
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    Article
  11. 311

    Adaptive Particle Swarm Optimization with Landscape Learning for Global Optimization and Feature Selection by Khalil Abbal, Mohammed El-Amrani, Oussama Aoun, Youssef Benadada

    Published 2025-01-01
    “…Particle swarm optimization (PSO), an important solving method in the field of swarm intelligence, is recognized as one of the most effective metaheuristics for addressing optimization problems. …”
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  12. 312
  13. 313

    A multi-objective optimization-based ensemble neural network wind speed prediction model by Haoyuan Ma, Chang Liu, Ziyuan Qiao, Yuan Liang, Hongqing Wang

    Published 2025-09-01
    “…Built upon the NSGA-II framework, NS-ADPOA enhances offspring generation by leveraging a probabilistic error-driven fusion of Particle Swarm Optimization (PSO) and Whale Optimization Algorithm (WOA), combining their strengths in local and global search, respectively. …”
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    Article
  14. 314

    Optimal Design of Short Fiber Bragg Grating Using Bat Algorithm With Adaptive Position Update by Ahmed Al-Muraeb, Hoda Abdel-Aty-Zohdy

    Published 2016-01-01
    “…We propose a new method to optimally design short triangular-spectrum fiber Bragg gratings (TS-FBGs), using the metaheuristic bat algorithm (BA). …”
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    Article
  15. 315

    An African vulture optimization algorithm based energy efficient clustering scheme in wireless sensor networks by Mohit Kumar, Ashwani Kumar, Sunil Kumar, Piyush Chauhan, Shitharth Selvarajan

    Published 2024-12-01
    “…To overcome the problem of energy depletion in WSN, this paper proposes a new Energy Efficient Clustering Scheme named African Vulture Optimization Algorithm based EECS (AVOACS) using AVOA. …”
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    Article
  16. 316

    The Active and Reactive Power Generation Reduction Based on Optimal location of UPFC Based on Genetic Algorithm by Sana Khalid Abd Al Hassan, Firas Mohammed Tuaimah, Yasser Nadhum Abd, Ali Adil Al-Lami

    Published 2025-07-01
    “… The Unified Power Flow Controller (UPFC) is a most complex power electronic device, which can simultaneously control a local bus voltage and optimize power flows in the electrical power transmission system. …”
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    Article
  17. 317

    Overlapping community-based fair influence maximization under a multi-transformation optimization algorithm by Chunfeng Jiang, Zegang Niu, Jingru Qu, Yulan Zhao, Amin Rezaeipanah

    Published 2025-05-01
    “…Specifically, the proposed algorithm demonstrates a 9.2% improvement in average influence spread over the best existing method, while effectively addressing the trade-offs between influence, fairness, and complexity.…”
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    Article
  18. 318

    Multiscale Modeling and Reconstruction of Joint Motion: Finite Element Optimization Based on Particle Swarm Algorithm by Jiaju Zhu, Zhong Zhang, Runnan Liu, Meixue Ren, Guodong Ma

    Published 2025-01-01
    “…Additionally, iterative reconstruction decreased the error in the knee region by approximately 30% compared to non-iterative methods. The optimization process facilitated by the particle swarm algorithm revealed that most particles achieved high fitness levels after the initial iteration, and a considerable proportion shifted to the foreground region during the second iteration once fitness values dropped below 0.2. …”
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  19. 319

    Meta-transformer: leveraging metaheuristic algorithms for agricultural commodity price forecasting by G. H. Harish Nayak, Md. Wasi Alam, B. Samuel Naik, B. S. Varshini, G. Avinash, Rajeev Ranjan Kumar, Mrinmoy Ray, K. N. Singh

    Published 2025-05-01
    “…To address these challenges, this study proposes a novel framework that combines Transformer models with Metaheuristic Algorithms (MHAs), including the Grey Wolf Optimizer (GWO), Whale Optimization Algorithm (WOA), and Particle Swarm Optimization (PSO) to enhance agricultural price forecasting accuracy. …”
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    Article
  20. 320

    A Shortest Distance Priority UAV Path Planning Algorithm for Precision Agriculture by Guoqing Zhang, Jiandong Liu, Wei Luo, Yongxiang Zhao, Ruiyin Tang, Keyu Mei, Penggang Wang

    Published 2024-11-01
    “…To address these challenges, this study proposes an enhanced Q-learning algorithm designed to optimize UAV path planning by combining static and dynamic obstacle avoidance features. …”
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    Article