Showing 2,881 - 2,900 results of 5,934 for search '(whole OR while) (optimizer OR optimize) algorithm', query time: 0.29s Refine Results
  1. 2881

    The outcome prediction method of football matches by the quantum neural network based on deep learning by Yang Sun, Hongyang Chu

    Published 2025-06-01
    “…During the model training phase, gradient descent is used to optimize weight parameters, and quantum algorithms are integrated to continuously adjust network weights to minimize prediction errors. …”
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    Article
  2. 2882

    Performance Evaluation of Hybrid Bio-Inspired and Deep Learning Algorithms in Gene Selection and Cancer Classification by Shahad S. Alkamli, Hala M. Alshamlan

    Published 2025-01-01
    “…Hybrid bio-inspired methods, inspired by natural optimization processes, have demonstrated significant advantages in navigating high-dimensional genomic data. …”
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    Article
  3. 2883

    Resource allocation strategies and task scheduling algorithms for cloud computing: A systematic literature review by Kareem Awad Waleed, Zainol Ariffin Khairul Akram, Nazri Mohd Zakree Ahmad, Yassen Esam Taha

    Published 2025-05-01
    “…It evaluates popular algorithms designed to optimize key metrics such as energy consumption, resource utilization, cost reduction, makespan minimization, and performance satisfaction. …”
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    Article
  4. 2884

    Integrated transportation system planning with gravitational search algorithm approach based on fuzzy mutant controller by Alireza Hosseinzadeh Kashani, Seyed Ahmad Shayannia, Mohammad Mehdi Movahedi, Soheila Sardar

    Published 2025-03-01
    “…In functions F1, F2, F15, the best results are observed in the gravitational particle population algorithm, while for functions F13, F14, the best results are observed in the particle population optimizer algorithm, and in F9, the real inheritance algorithm has better performance. …”
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    Article
  5. 2885

    Multiradar Collaborative Task Scheduling Algorithm Based on Graph Neural Networks with Model Knowledge Embedding by Haoqing LI, Dian YU, Changchun PAN, Wenxian YU, Dongying LI

    Published 2025-04-01
    “…A key innovation of this algorithm is its capability to capture critical model knowledge using low-complexity calculations, which helps to further optimize the GNN model. …”
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    Article
  6. 2886

    Genetic Algorithm and Mathematical Modelling for Integrated Schedule Design and Fleet Assignment at a Mega-Hub by Melis Tan Tacoglu, Mustafa Arslan Ornek, Yigit Kazancoglu

    Published 2025-06-01
    “…Second, a genetic algorithm (GA) was employed to demonstrate scalability and flexibility, delivering near-optimal, high-granularity schedules with significantly reduced computational time. …”
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    Article
  7. 2887

    An energy-saving virtual machine scheduling algorithm for resource management based on cloud computing technology by Liangyu Zhang

    Published 2025-04-01
    “…Therefore, the algorithm proposed in this paper can effectively reduce energy consumption while avoiding frequent migration of virtual machines, and the innovation in genetic algorithm optimization strategy improves the overall efficiency and stability of scheduling.…”
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    Article
  8. 2888

    Quantitative study on weak magnetic detection defects of metal structure based on IWOA-BP algorithm by FAN Meng, TONG Bo, GAO Chen, YAO Zhongyuan, ZHANG Yu, HU Bo

    Published 2025-03-01
    “…In view of the poor effect and low efficiency of BP neural network in parameter adjustment, the improved whale optimization algorithm (IWOA) based on Sine chaotic mapping was adopted to optimize the BP neural network parameter adjustment mode, giving consideration to global optimization while improving the local optimization ability, and then the optimal parameters searched by IWOA were assigned to BP neural network, improving the quality of initial network parameters.The length, width and depth of the artificial rectangular slot were quantified by inversion. …”
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    Article
  9. 2889

    Combining the A* Algorithm with Neural Networks to Solve the Team Orienteering Problem with Obstacles and Environmental Factors by Alfons Freixes, Javier Panadero, Angel A. Juan, Carles Serrat

    Published 2025-05-01
    “…To achieve this, we employ a simheuristic algorithm for the overall route optimization, while integrating the A* algorithm to determine feasible paths between nodes that avoid obstacles in a 2D grid-based environment. …”
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    Article
  10. 2890

    Review on Maximum Power Point Tracking Control Strategy Algorithms for Offshore Floating Photovoltaic Systems by Lei Huang, Baoyi Pan, Shaoyong Wang, Yingrui Dong, Zihao Mou

    Published 2024-11-01
    “…This paper provides a thorough review of MPPT techniques applicable to floating photovoltaic systems, evaluating the suitability of various methods under marine conditions. Traditional algorithms require modifications to address the drift phenomena under uniform irradiation, while different GMPPT techniques exhibit distinct strengths and limitations in partial shading conditions (PSCs). …”
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    Article
  11. 2891

    Enhanced electric vehicle battery management system employing bat algorithm with chaotic diversification strategies by Batchu Veena Vani, Dharavath Kishan, Md Waseem Ahmad, Ch. Rama Prakasha Reddy

    Published 2024-11-01
    “…This article presents a method using the Bat Algorithm (BA) improved by chaotic diversification as well as social education to optimize the power source replacement and the electric vehicle charging procedure. …”
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    Article
  12. 2892

    Disease Detection Algorithm for Tea Health Protection Based on Improved Real-Time Detection Transformer by Zhijie Lin, Zilong Zhu, Lingling Guo, Jingjing Chen, Jiyi Wu

    Published 2025-02-01
    “…Faster-LTNet employs partial convolution and hierarchical design to optimize computational resources, while the CG Attention Module enhances multi-head self-attention by introducing grouped feature inputs and cascading operations to reduce redundancy and increase attention diversity. …”
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    Article
  13. 2893

    Novel algorithm for multifocus image fusion: integration of convolutional neural network and partial differential equation by Gargi J Trivedi, Rajesh Sanghvi

    Published 2024-04-01
    “…Furthermore, we aim to enhance our approach by incorporating machine learning techniques to optimize the parameters of the image fusion algorithm. …”
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    Article
  14. 2894

    Lightweight Transformer traffic scene semantic segmentation algorithm integrating multi-scale depth convolution by Gang XIE, Quanyi WANG, Xinlin XIE, Jian’an WANG

    Published 2023-10-01
    “…Aiming at the problems of discontinuous segmentation of thin strip objects that were easy to blend into the surrounding background and a large number of model parameters in the semantic segmentation algorithm of traffic scenes, a lightweight Transformer traffic scene semantic segmentation algorithm integrating multi-scale depth convolution was proposed.First, a multi-scale strip feature extraction module (MSEM) was constructed based on deep convolution to enhance the representation ability of thin strip target features at different scales.Secondly, a spatial detail auxiliary module (SDAM) was designed using the convolutional inductive bias feature in the shallow network to compensate for the loss of deep spatial detail information to optimize object edge segmentation.Finally, an asymmetric encoding-decoding network based on the Transformer-CNN framework (TC-AEDNet) was proposed.The encoder combined Transformer and CNN to alleviate the loss of detail information and reduce the amount of model parameters; while the decoder adopted a lightweight multi-level feature fusion design to further model the global context.The proposed algorithm achieves the mean intersection over union (mIoU) of 78.63% and 81.06% respectively on the Cityscapes and CamVid traffic scene public datasets.It can achieve a trade-off between segmentation accuracy and model size in traffic scene semantic segmentation and has a good application prospect.…”
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  15. 2895

    Short-Term Electric Load Forecasting for an Industrial Plant Using Machine Learning-Based Algorithms by Oğuzhan Timur, Halil Yaşar Üstünel

    Published 2025-02-01
    “…The integration of calendar, meteorological, and lagging electrical variables, along with machine learning-based algorithms, is employed to boost forecasting accuracy and optimize energy utilization. …”
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    Article
  16. 2896

    GVDF-RRT*: An Improved F-RRT* Path Planning Algorithm Based on Generalized Voronoi Diagram by Yitao Zhong, Xiaojing Zhu, Jianfang Huang, Yaokun Ye, Zhaoming Wang, Yuhuai Wang

    Published 2025-01-01
    “…Secondly, a node direct connection mechanism is established, which reduces the redundant computation and further reduces the initial time by hierarchical processing of creation nodes, while combined with the forward optimization mechanism to optimize the paths in iteration, effectively reducing the path cost. …”
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    Article
  17. 2897

    Reliable and efficient magnetic data inversion for resource detection using a hybrid bat algorithm by Khalid S. Essa, Mahmoud Elhussein, Omar A. Gomaa, Zein E. Diab

    Published 2025-07-01
    “…This study introduces an innovative hybrid algorithm integrating the Bat Algorithm (BA) with the Fourth Horizontal Gradient (FHG) to optimize the estimation of geometric parameters (depth, amplitude coefficient, shape factor, source origin, and magnetization angle) from magnetic field data. …”
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    Article
  18. 2898

    The A3C Algorithm With Eligibility Traces of Energy Management for Plug-In Hybrid Electric Vehicles by Dingyi Guo, Guangyin Lei, Huichao Zhao, Fang Yang, Qiang Zhang

    Published 2025-01-01
    “…A mathematical formulation of the energy management problem is proposed to optimize fuel consumption while adhering to the vehicle’s operational constraints. …”
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    Article
  19. 2899

    Enhancing Youbike Redistribution System: A Study on Station Recommendation Using a Genetic Algorithm by Yang-Chou Juan, Yi-Chung Chen, Wei-Ting Chen, Chieh Yang, Chia-Tzu Liu, Yi-Ci Hou, Yi-Hsuan Tsai

    Published 2025-02-01
    “…A random forest model selected key crowd grid factors as input variables for a long short-term memory (LSTM) prediction model to accurately predict demand patterns, including during special events or weather changes. A genetic algorithm then determined optimal station configurations and provided return station recommendations, considering user destinations and station dock ratios, while minimizing manual redistribution. …”
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    Article
  20. 2900