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Showing 201 - 220 results of 346 for search '(improved OR improve) ((coot OR post) OR root) optimization algorithm', query time: 0.15s Refine Results
  1. 201

    Time-Variation Damping Dynamic Modeling and Updating for Cantilever Beams with Double Clearance Based on Experimental Identification by Yunhe Zhang, Fanjun Meng, Xueguang Li, Wei Song, Dashun Zhang, Faping Zhang

    Published 2025-01-01
    “…The quantum genetic algorithm (QGA) is used to optimize the scale factor, which determines the identification accuracy and calculation efficiency. …”
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  2. 202
  3. 203

    An Enhanced Generative Adversarial Network Prediction Model Based on LSTM and Attention for Corrosion Rate in Pipelines by Pujun Long, Mi Liang, Hongjian Chen, Qin Yang

    Published 2025-01-01
    “…This model integrates an improved Generative Adversarial Network with Grey Wolf Optimization and Support Vector Regression (LAGAN-GWO-SVR). …”
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  4. 204

    Integrating vision transformer-based deep learning model with kernel extreme learning machine for non-invasive diagnosis of neonatal jaundice using biomedical images by M. Eliazer, Sibi Amaran, K. Sreekumar, A. Vikram, Gyanendra Prasad Joshi, Woong Cho

    Published 2025-07-01
    “…Finally, the enhanced coati optimization algorithm (ECOA) method is implemented for the hyperparameter tuning of the KELM method, which results in a higher classification process. …”
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    Article
  5. 205

    Anomaly Detection Using Machine Learning in Hydrochemical Data From Hot Springs: Implications for Earthquake Prediction by Ruijie Zhu, Fengtian Yang, Xiaocheng Zhou, Jiao Tian, Yongxian Zhang, Miao He, Jingchao Li, Jinyuan Dong, Ying Li

    Published 2024-06-01
    “…Despite limitations such as the inability to differentiate pre‐earthquake anomalies from post‐earthquake anomalies and pinpoint the precise location of earthquakes, this study successfully showcases the potential of machine learning algorithms in earthquake prediction, paving the way for further research and improved prediction methods.…”
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    Article
  6. 206

    State of charge estimation of lithium-ion batteries in an electric vehicle using hybrid metaheuristic - deep neural networks models by Zuriani Mustaffa, Mohd Herwan Sulaiman, Jeremiah Isuwa

    Published 2025-06-01
    “…This study proposes a novel approach for SoC estimation in BMW EVs by integrating a metaheuristic algorithm with deep neural networks. Specifically, teaching-learning based optimization (TLBO) is employed to optimize the weights and biases of the deep neural networks model, enhancing estimation accuracy. …”
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    Article
  7. 207

    Seasonally Adaptive VMD-SSA-LSTM: A Hybrid Deep Learning Framework for High-Accuracy District Heating Load Forecasting by Yu Zhang, Keyong Hu, Lei Lu, Qingqing Yang, Min Fang

    Published 2025-07-01
    “…To improve the accuracy of heating load forecasting and effectively address the energy waste caused by supply–demand imbalances and uneven thermal distribution, this study innovatively proposes a hybrid prediction model incorporating seasonal adjustment strategies. …”
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  8. 208

    Random PWM Technique Based Two-State Markov Chain for Permanent Magnet Synchronous Motor Control by Zhiqiang Wang, Xinyuan Liu, Xuefeng Jin, Guozheng Zhang, Zhichen Lin

    Published 2025-04-01
    “…Secondly, to address the problem of insufficient random performance in the traditional RPWM technique, an innovative optimization scheme is proposed, i.e., the introduction of a two-state Markov chain and, based on the immune algorithm for transition probability and random gain, the optimization of two key parameters. …”
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    Article
  9. 209
  10. 210

    Method and experimental verification of spatial attitude prediction for an advanced hydraulic support system under mining influence by Zhuang Yin, Kun Zhang, ZengBao Zhang, Hongyue Chen, Lingyu Meng, Zhen Wang, Mingchao Du, Xiangpeng Hu, Defu Zhao, Dan Tian

    Published 2025-07-01
    “…Based on this, the WOA algorithm was utilized to search for the optimal number of neurons in the hidden layer and the learning rate. …”
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    Article
  11. 211

    Enhancing Hajj and Umrah Services Through Predictive Social Media Classification by Samia Allaoua Chelloug, Mohammed Saleh Ali Muthanna, Faisal Jamil, Mehdhar S. A. M. Al-Gaashani, Soha Alhelaly, Ahmed Aziz, Ammar Muthanna

    Published 2025-01-01
    “…The primary objective of this system is to efficiently classify and analyze social media content related to Hajj and Umrah services. To improve the effectiveness of this classification model, we introduce a predictive optimization strategy that employs a deep neural network as the learning module and utilizes particle swarm optimization to refine the weighting parameters. …”
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    Article
  12. 212

    CPO-VMD Combined With Multiscale Permutation Entropy for Noise Reduction in GNSS Vertical Time Series in Mining Areas by Xu Yang, Xinxin Yao, Xinjian Fang, Xuexiang Yu, Yi Wu, Shicheng Xie

    Published 2025-01-01
    “…The method uses the CPO algorithm to optimize the key parameters of the VMD, determines the high-frequency components with MPE values higher than a set threshold as noise components and removes them, and then reconstructs the remaining components in order to obtain the noise-reduced time series. …”
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  13. 213

    INFO-RF-based fault diagnosis and analysis method for busbars by Chen Xue, Jian Zhu, Haiou Cao, Yan Gu, Siyu Chen

    Published 2025-07-01
    “…A simulation model of a dual-busbar power system is first established, and key electrical quantities such as differential current, bus tie current, and voltage are extracted to quantify fault features using Root Mean Square (RMS) values. The RF model is then used to predict fault types and fault resistance, with the INFO algorithm iteratively optimizing the hyperparameters of the RF model to further improve prediction accuracy. …”
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  14. 214

    Interactive online learning method for students based on artificial intelligence by Cizhang Li, Wenfen Yin

    Published 2025-08-01
    “…This study proposes a novel approach that integrates the Dwarf Mongoose Optimization (DMO) algorithm with a Gated Recurrent Unit (GRU) neural network to develop an AI-powered interactive online learning model. …”
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  15. 215

    New method for landslide susceptibility evaluation in alpine valley regions that considers the suitability of InSAR monitoring and introduces deformation rate grading by Dingyi Zhou, Zhifang Zhao, Wenfei Xi, Xin Zhao, Jiangqin Chao

    Published 2025-03-01
    “…The landslide susceptibility model is developed utilizing the Particle Swarm Optimization-Back Propagation (PSO-BP) algorithm. It includes evaluation techniques for regions without deformation rates. …”
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  16. 216

    SABO-ELM model for remaining life prediction of lithium-ion batteries under multiple health factors by Jiabo LI, Zhonglin SUN, Di TIAN, Zhixuan WANG

    Published 2025-06-01
    “…The SABO algorithm optimizes the weights and bias thresholds of the ELM model, which effectively reduces the risk of local optima and improves its predictive performance and stability. …”
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  17. 217
  18. 218

    Energy storage efficiency modeling of high-entropy dielectric capacitors using extreme learning machine and swarm-based hybrid support vector regression computational methods by Yas Al-Hadeethi, Taoreed O. Owolabi, Mouftahou B. Latif, Bahaaudin M. Raffah, Ahmad H. Milyani, Saheed A. Tijani

    Published 2025-09-01
    “…The developed sigmoid (SG) activation function-based ELM (SG-ELM) shows performance improvement over sine (SI) function-based ELM (SI-ELM) model and PS-SVR model with an improvement of 79.25 % and 89.4 % using root mean square error (RMSE) performance measuring parameter. …”
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  19. 219

    An Integrated Approach to the Determination of Wages of Bank Employees by Alexander S. Artamonov

    Published 2017-11-01
    “…The integrated approach that was used to calculate the wages of employees of the bank employees taking into account the proposed comparison algorithm with market data on wages submitted by the consulting companies, may potentially contribute to improving the competitiveness of HR-brand of the organization and optimize the size of the wage fund.…”
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  20. 220