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  1. 221
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    THE ALGORITHMIC MODEL OF LABORATORY DIAGNOSTICS OPTIMIZATION by G. I. Nazarenko, O. V. Andropova

    Published 2015-12-01
    “…Various algorithmic models, their features and structure are reviewed. …”
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    Article
  3. 223

    Parameter Optimization of MALDI-TOF MS Based on Improved Whale Optimization Algorithm by Yu-peng ZHANG, Yu-gong DANG, Hui-yuan YANG, Zhi-gang ZHOU, Gao-hang JIANG

    Published 2025-05-01
    “…To address the shortcomings of the Whale optimization algorithm, including slow convergence speed, low precision and susceptibility to local optima, improvements were made on the convergence factor, inertia weight and position update strategy. …”
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    Article
  4. 224
  5. 225

    PREDICTION OF TBM OIL TEMPERATURE BY IMPROVED CAMEL ALGORITHM ASSISTED RANDOM FOREST MODEL (MT) by REN JianJi, ZHAO RunQiu, WANG ZhenXi, LIU YuMing, YUAN YongLiang

    Published 2023-01-01
    “…Secondly, the improved camel algorithm was used to optimize the parameters of the TBM oil temperature prediction model established by the random forest to obtain the best model. …”
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    Article
  6. 226

    Multi-objective Optimization Configuration of Capacitor Blocking Devices Based on Field-Circuit Coupled Model and Improved Differential Evolution Algorithm by Hongwei LIU

    Published 2020-08-01
    “…Based on the operating characteristics of the DC blocking devices, this paper analyzes the influence of the DC blocking devices on the DC current near the neutral point of the transformers, and proposes a multi-objective optimization configuration method for capacitor blocking devices based on the field-circuit coupling model and improved differential evolution algorithm. …”
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    Article
  7. 227
  8. 228

    Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting by Peng Wei, Wang Yu

    Published 2025-01-01
    “…To evaluate the predictive capability, the models are compared with quantum bee colony algorithm-optimized AI models (QABC-SVR and QABC-ANN), genetic algorithm-optimized AI models (GA-SVR and GA-ANN) and traditional AI models (SVR and ANN). …”
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    Article
  9. 229

    A New Hyperparameter Tuning Framework for Regression Tasks in Deep Neural Network: Combined-Sampling Algorithm to Search the Optimized Hyperparameters by Nguyen Huu Tiep, Hae-Yong Jeong, Kyung-Doo Kim, Nguyen Xuan Mung, Nhu-Ngoc Dao, Hoai-Nam Tran, Van-Khanh Hoang, Nguyen Ngoc Anh, Mai The Vu

    Published 2024-12-01
    “…The primary goal is to improve hyperparameter tuning performance in deep learning models compared to conventional methods such as Bayesian Optimization and Random Search. …”
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    Article
  10. 230

    Volt/VAr Regulation of the West Mediterranean Regional Electrical Grids Using SVC/STATCOM Devices With Neural Network Algorithms by H. Feza Carlak, Ergin Kayar

    Published 2025-02-01
    “…A load flow and short circuit analysis is performed on the designed transmission system for a number of critical scenarios. The modeled power system is optimized for the size and location of the FACTS devices by applying genetic algorithms (GAs) and particle swarm optimization (PSO) algorithms to the selected busbars of the FACTS devices, a strategy designed to significantly reduce system losses. …”
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    Article
  11. 231

    Soil water content estimation by using ground penetrating radar data full waveform inversion with grey wolf optimizer algorithm by M. H. Zhang, X. Feng, M. Bano, C. Liu, Q. Liu, X. Wang

    Published 2025-01-01
    “…Full waveform inversion (FWI) can use the information of the entire waveform, which can improve the accuracy of parameter estimation. This study proposes a novel SWC estimation scheme by using the FWI of GPR, optimized by the grey wolf optimizer (GWO) algorithm. …”
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    Article
  12. 232

    Improved grey wolf optimization algorithm based service function chain mapping algorithm by Yue ZHANG, Junnan ZHANG, Xiaochun WU, Chen HONG, Jingjing ZHOU

    Published 2022-11-01
    “…With the rise of new Internet applications such as the industrial Internet, the Internet of vehicles, and the metaverse, the network’s requirements for low latency, reliability, security, and certainty are facing severe challenges.In the process of virtual network deployment, when using network function virtualization technology, there were problems such as low service function chain mapping efficiency and high deployment resource overhead.The node activation cost and instantiation cost was jointly considered, an integer linear programming model with the optimization goal of minimizing the average deployment network cost was established, and an improved grey wolf optimization service function chain mapping (IMGWO-SFCM) algorithm was proposed.Three strategies: mapping scheme search based on acyclic KSP algorithm, mapping scheme coding and improvement based on reverse learning and nonlinear convergence were added to the standard grey wolf optimization algorithm to form this algorithm.The global search and local search capabilities were well balanced and the service function chain mapping scheme was quickly determined by IMGWO-SFCM.Compared with the comparison algorithm, IMGWO-SFCM reduces the average deployment network cost by 11.86% while ensuring a higher service function chain request acceptance rate.…”
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  13. 233

    Chain hybrid feature selection algorithm based on improved Grey Wolf Optimization algorithm. by Xiaotong Bai, Yuefeng Zheng, Yang Lu, Yongtao Shi

    Published 2024-01-01
    “…It also shows that the algorithm improves the generalization ability and performance of the model.…”
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    Article
  14. 234

    Enhancing PM<sub>2.5</sub> Air Pollution Prediction Performance by Optimizing the Echo State Network (ESN) Deep Learning Model Using New Metaheuristic Algorithms by Iman Zandi, Ali Jafari, Aynaz Lotfata

    Published 2025-04-01
    “…This study evaluates efficient metaheuristic algorithms for optimizing deep learning model hyperparameters to improve the accuracy of PM<sub>2.5</sub> concentration predictions. …”
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    Article
  15. 235

    Relaxation Parameter Optimization in Electrical-to-Mechanical Co-Simulation Based on Time Windowing WR Technique by Md Moktarul Alam, Richard Perdriau, Mohammed Ramdani, Mohsen Koohestani

    Published 2025-01-01
    “…This paper presents an innovative approach to enhancing the time windowing waveform relaxation (WR) technique in electrical-to-mechanical co-simulation by optimizing relaxation parameters for improved performance. …”
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    Article
  16. 236

    AquaFlowNet a machine learning based framework for real time wastewater flow management and optimization by P. Prabu, Ala Saleh Alluhaidan, Romana Aziz, Shakila Basheer

    Published 2025-05-01
    “…However, most existing methods rely on static or rule-based models, which lack the flexibility to handle fluctuating flow rates, variable environmental loads, and unforeseen disruptions. …”
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    Article
  17. 237

    Improved Particle Swarm Optimization Algorithm Optimize the Control Strategy of Family Energy Management System by WEI Qi, LI Shi-nan, ZHU Ying-ying

    Published 2018-04-01
    “…In order to better respond accding to the demand of TOU price control project management of family family load and energy,put forward the household electricity load control strategy,based on analysis of the existing household electricity load control strategies,using improved particle swarm optimization algorithm for the control strategy optimization target,the establishment of a single-user,multi-user household electricity control optimization model,In the MATLAB platform,the results of optimization algorithm are analyzed by simulation. …”
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  18. 238

    Dynamic Path Optimization Based on Improved Ant Colony Algorithm by Juan Cheng

    Published 2023-01-01
    “…Aiming at the shortcomings of the current dynamic path optimization method, the improved ant colony algorithm was used to optimize the dynamic path. …”
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    Article
  19. 239

    Using BERT and ZFNet/ELM optimized by improved Orca optimization algorithm for sentiment analysis by Jun Yang, Jafar Safarzadeh

    Published 2025-04-01
    “…Then, the data were inserted into ZFNet/ELM, which was optimized by Improved Orca Optimization Algorithm (IOPA). …”
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