Search alternatives:
improve model » improved model (Expand Search)
cost » most (Expand Search)
post » most (Expand Search)
Showing 1,721 - 1,740 results of 7,994 for search '(( improved (cost OR post) optimization algorithm ) OR ( improve model optimization algorithm ))', query time: 0.44s Refine Results
  1. 1721

    Optimization of Business English Teaching Based on the Integration of Interactive Virtual Reality Genetic Algorithm by Xiao Ma

    Published 2022-01-01
    “…The results of the simulation experiment indicate that the improved algorithm designed in this article can reduce the computational overhead of the meta-algorithm to a great extent, and the improvement strategy is designed based on the evaluation results of practical examples.…”
    Get full text
    Article
  2. 1722

    Quality of service optimization algorithm based on deep reinforcement learning in software defined network by Cenhuishan LIAO, Junyan CHEN, Guanping LIANG, Xiaolan XIE, Xiaoye LU

    Published 2023-03-01
    “…Deep reinforcement learning has strong abilities of decision-making and generalization and often applies to the quality of service (QoS) optimization in software defined network (SDN).However, traditional deep reinforcement learning algorithms have problems such as slow convergence and instability.An algorithm of quality of service optimization algorithm of based on deep reinforcement learning (AQSDRL) was proposed to solve the QoS problem of SDN in the data center network (DCN) applications.AQSDRL introduces the softmax deep double deterministic policy gradient (SD3) algorithm for model training, and a SumTree-based prioritized empirical replay mechanism was used to optimize the SD3 algorithm.The samples with more significant temporal-difference error (TD-error) were extracted with higher probability to train the neural network, effectively improving the convergence speed and stability of the algorithm.The experimental results show that the proposed AQSDRL effectively reduces the network transmission delay and improves the load balancing performance of the network than the existing deep reinforcement learning algorithms.…”
    Get full text
    Article
  3. 1723

    SMOTE algorithm optimization and application in corporate credit risk prediction with diversification strategy consideration by Han Wei

    Published 2025-07-01
    “…Empirical results demonstrate the optimized SMOTE algorithm’s superiority over six comparison models, such as random over-sampling, under-sampling, etc. …”
    Get full text
    Article
  4. 1724

    Research on Static/Dynamic Global Path Planning Based on Improved A∗ Algorithm for Mobile Robots by Huifang Bao, Jie Fang, Chaohai Wang, Zebin Li, Jinsi Zhang, Chuansheng Wang

    Published 2023-01-01
    “…In addition, we combine the improved A∗ algorithm with the dynamic window algorithm to enable mobile robots to realize real-time dynamic obstacle avoidance while ensuring the optimality of global path planning.…”
    Get full text
    Article
  5. 1725

    Optimizing Crop Yield Prediction: An In-Depth Analysis of Outlier Detection Algorithms on Davangere Region by C. S. Anu, C. R. Nirmala, A. Bhowmik, A. Johnson Santhosh

    Published 2025-01-01
    “…This method demonstrated improved performance in refining the crop yield prediction model by identifying and removing outliers, thereby contributing to more accurate predictions and optimized planning in the dynamic landscape of the Davangere region.…”
    Get full text
    Article
  6. 1726

    Fruit-Fly-Optimized Weighted Averaging Algorithm for Data Fusion in MEMS IMU Array by Ting Zhu, Gao Peng, Jianping Li, Jiawei Xuan, Jingbei Tian

    Published 2025-06-01
    “…In this study, an optimal weighted averaging algorithm based on the fruit fly optimization algorithm (FOA) is proposed by analyzing the data fusion mechanism of the MEMS IMU array. …”
    Get full text
    Article
  7. 1727

    Multi-objective optimization of dual-stator permanent magnet motor based on composite algorithm by Xiaoguang Kong, Zhuo Yang

    Published 2025-07-01
    “…Then, the Taguchi method optimizes the significant variables, the genetic algorithm based on the Kriging response surface model optimizes the non-significant variables, and finally, the optimal solution is selected on the Pareto front. …”
    Get full text
    Article
  8. 1728

    Portfolio optimization with MOPSO-Shrinkage hybrid model by Minh Tran, Nhat M. Nguyen

    Published 2025-06-01
    “…Unlike traditional shrinkage covariance models, which struggle in highly dynamic environments, our hybrid model optimally selects stocks and improves risk-adjusted returns. …”
    Get full text
    Article
  9. 1729

    An Enhanced Genetic Algorithm for Optimized Educational Assessment Test Generation Through Population Variation by Doru-Anastasiu Popescu

    Published 2025-04-01
    “…The most important aspect of a genetic algorithm (GA) lies in the optimal solution found. …”
    Get full text
    Article
  10. 1730

    Optimization of the control system of BP-PID rice polishing unit based on WAO algorithm by HUANG Jinliang, ZHOU Jin, YU Wei

    Published 2024-11-01
    “…ObjectiveAddress the current issues of poor internal flow stability, low single-machine efficiency, and subpar polishing quality in rice polishing units.MethodsFirstly, the traditional polishing machine was improved, its control parameters were clarified, and the mathematical model of the rice polishing unit was established. …”
    Get full text
    Article
  11. 1731

    Retracted: VR Panorama Mosaic Algorithm Based on Particle Swarm Optimization and Mutual Information by Zhonggao Yang, Dan Xiang, Yili Cheng

    Published 2020-01-01
    “…This algorithm is based on particle swarm optimization, combined with the advantages of traditional mutual information algorithm, according to the characteristics of virtual reality imaging, a new model is established. …”
    Get full text
    Article
  12. 1732
  13. 1733
  14. 1734

    Emergency Scheduling Optimization Simulation of Cloud Computing Platform Network Public Resources by Dingrong Liu, Zhigang Yao, Liukui Chen

    Published 2021-01-01
    “…An emergency scheduling method of cloud computing platform network public resources based on genetic algorithm is proposed. With emergency public resource scheduling time cost and transportation cost minimizing target, initial population by Hamming distance constraints, emergency scheduling model, and the corresponding objective function improvement as the fitness function, the genetic algorithm to individual selection and crossover and mutation probability were optimized and complete the public emergency resources scheduling. …”
    Get full text
    Article
  15. 1735

    Research on the optimization of optimal blasting parameters and fragmentation control based on coal seam geological conditions by Zhouquan Liao, Xiaohua Ding, Mingzhi Liang, Jiangfeng Li, Zhongao Yang, Xin Liu, Bin Li, Yan Zhang

    Published 2025-04-01
    “…Abstract Open-pit coal mining often employs loosening blasting, with perforation blasting accounting for a significant portion of the coal seam mining costs. For coal of the same quality, the price of lump coal is much higher than that of crushed coal. …”
    Get full text
    Article
  16. 1736
  17. 1737

    Determination of Optimal Parameters of the Ground Filling During the Laying of Power Cable Lines by M. E. Vysotski

    Published 2025-04-01
    “…To solve the optimization problem, a genetic algorithm implemented in the MS Excel environment was used. …”
    Get full text
    Article
  18. 1738

    Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization by Yuzhi YAN, Youming LI, Guili ZHOU, Yaohui WU

    Published 2016-11-01
    “…Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate,but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance,a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm,the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal,which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy,but also reduces time and communication costs of the sensing process,and improves the spectrum sensing performance.…”
    Get full text
    Article
  19. 1739

    Wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization by Yuzhi YAN, Youming LI, Guili ZHOU, Yaohui WU

    Published 2016-11-01
    “…Wideband distributed cooperative spectrum sensing based on compressed sensing can not only reduce high sampling rate,but also improve the spectrum sensing performance in low signal to noise ratio environment.In order to further enhance the spectrum sensing performance,a wideband distributed cooperative compressed spectrum sensing algorithm based on weighted consensus optimization was proposed.In this algorithm,the next iterative reconstruction weights were determined according to the current iterative reconstructed spectrum signal,which can encourage the sub-band occupied by primary user to generate signal value and decrease the likelihood of incorrect reconstruction.Simulation results show that the proposed algorithm can not only increases the spectral reconstruction accuracy,but also reduces time and communication costs of the sensing process,and improves the spectrum sensing performance.…”
    Get full text
    Article
  20. 1740

    Management and prediction of river flood utilizing optimization approach of artificial intelligence evolutionary algorithms by Rana Muhammad Adnan Ikram, Mo Wang, Hossein Moayedi, Atefeh Ahmadi Dehrashid

    Published 2025-07-01
    “…These evolutionary algorithms simulate natural processes like selection, mutation, and crossover to optimize flood predictions and management strategies, improving adaptability in dynamic environments. …”
    Get full text
    Article