Showing 201 - 220 results of 1,750 for search '(( improve most optimization algorithm ) OR ( improve root optimization algorithm ))', query time: 0.29s Refine Results
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    Flow direction algorithm for optimal coordination of directional overcurrent relays considering arc flash by Dina K. Mahmoud, Shady H.E.Abdel Aleem, Ahmed M. Ibrahim, Mahmoud M. Sayed, Wael Abdelfattah

    Published 2025-03-01
    “…This paper presents a novel meta-heuristic optimization method called flow direction algorithm (FDA) to achieve optimal coordination of Directional Overcurrent Relays (DOCRs) while considering the impact of Arc Flash (AF). …”
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    Article
  4. 204

    Optimization Design Method of Pipe-Insulating Joints Based on Surrogate Model and Genetic Algorithm by Chen Guo, Zheng Yang, Jianbo Dong, Yanchao Yue, Linjun Tian, Ping Ma

    Published 2025-07-01
    “…This improves the computational efficiency of the optimization algorithm by establishing a surrogate model, which can be used to optimize the dimensions of insulation joints.…”
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  5. 205

    Optimal scheduling method for multi-regional integrated energy system based on dynamic robust optimization algorithm and bi-level Stackelberg model by Bo Zhou, Erchao Li, Wenjing Liang

    Published 2025-06-01
    “…Finally, a combination algorithm of improved robust optimization over time (ROOT) and CPLEX is proposed to solve the established game model. …”
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    Article
  6. 206

    A novel solid waste instance creation for an optimized capacitated vehicle routing model using discrete smell agent optimization algorithm by Ahmed T. Salawudeen, Olusesi A. Meadows, Basira Yahaya, Muhammed B. Mu'azu

    Published 2024-12-01
    “…The developed model was optimized using a new discrete smell agent optimization (SAO) algorithm and compared to firefly algorithm (FA) and particle swarm optimization (PSO). …”
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  7. 207

    Image cluster algorithm of hybrid encoding method by Chun-hui ZHAO, Xue-yuan LI, Ying CUI

    Published 2017-02-01
    “…In the clustering analysis based on swarm intelligence optimization algorithm,the most of encoding method only used single form,and this method might be limit range of search space,the algorithm was easy to fall into local op-timum.In order to solve this problem,image clustering algorithm of hybrid encoding (HEICA) was proposed.Firstly,a hybrid encoding model based on image clustering was established,this method could expand the scope of the search space.Meanwhile,it was combined with two optimization algorithms which improved rain forest algorithm (IRFA) and quantum particle swarm optimization (QPSO),this method could improve the global search capability.In the simulation experiment,it was carried out to illustrate the performance of the proposed method based on four datasets.Compared with results form four measured cluster algorithm.The experimental results show that the algorithm has strong global search capability,high stability and clustering effect.…”
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    Machine-Learning-Algorithm-Assisted Portable Miniaturized NIR Spectrometer for Rapid Evaluation of Wheat Flour Processing Applicability by Yuling Wang, Chen Zhang, Xinhua Li, Longzhu Xing, Mengchao Lv, Hongju He, Leiqing Pan, Xingqi Ou

    Published 2025-05-01
    “…By employing an improved whale optimization algorithm (iWOA) coupled with a successive projections algorithm (SPA), we selected the 20 most informative wavelengths (MIWs) from the full range spectra, allowing the iWOA/SPA-SOA-SVR model to predict SV with correlation coefficient and root-mean-square errors in prediction (R<sub>P</sub> and RMSE<sub>P</sub>) of 0.9605 and 0.2681 mL. …”
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  10. 210

    An Improved MOEA/D Based on Reference Distance for Software Project Portfolio Optimization by Jing Xiao, Jing-Jing Li, Xi-Xi Hong, Min-Mei Huang, Xiao-Min Hu, Yong Tang, Chang-Qin Huang

    Published 2018-01-01
    “…In this paper, we propose an improved MOEA/D (multiobjective evolutionary algorithm based on decomposition) based on reference distance (MOEA/D_RD) to solve the software project portfolio optimization problems with optimizing 2, 3, and 4 objectives. …”
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    Optimizing RetinaNet anchors using differential evolution for improved object detection by Asaad Mohammed, Hosny M. Ibrahim, Nagwa M. Omar

    Published 2025-06-01
    “…Specifically, we propose an optimization algorithm based on Differential Evolution (DE) that adjusts anchor scales and ratios while determining the most appropriate number of these parameters for each dataset based on the annotated data. …”
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  14. 214

    Heuristic Optimization-Assisted Dilated Convolution Neural Network With Gated Recurrent Unit for Channel Estimation in NOMA-OFDM System by Vijayakumar Kondepogu, Budhaditya Bhattacharyya

    Published 2024-01-01
    “…The loss functions in the model are optimized by using the Improved Pelican Optimization Algorithm (IPOA). …”
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  15. 215

    Mobile Robot Path Planning Based on Enhanced Dynamic Window Approach and Improved A∗ Algorithm by Hongxia Yang, Xingqiang Teng

    Published 2022-01-01
    “…In the improved A∗ algorithm, in order to improve the algorithm efficiency, so that a single planning path can pass through multiple target points, the search point selection strategy and evaluation function are optimized. …”
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  16. 216

    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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  17. 217

    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
  18. 218

    Small Target Detection Algorithm for UAV Aerial Images Based on Improved YOLOv7-tiny by ZHANG Guanghua, LI Congfa, LI Gangying, LU Weidang

    Published 2025-05-01
    “…Removing the fourth small target detection head results in the most obvious performance degradation, reducing detection accuracy by 2.4%. 3) Comparative experiments are conducted to verify the comprehensive performance of the improved algorithm. …”
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    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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