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  1. 201

    Optimal Operation of Microgrid Based on Improved Particle Swarm Optimization Algorithm by Shaoming ZHANG, Siqing SHENG

    Published 2020-05-01
    “…Under same conditions, the optimal operation model of the microgrid is solved using the original algorithm and the improved algorithm respectively, and the superiority of the improved algorithm is verified by comparing the solution results.…”
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    Article
  2. 202

    Research on Interference Resource Optimization Based on Improved Whale Optimization Algorithm by Xuyi Chen, Mingxi Ma, Chengkui Liu, Haifeng Xie, Shaoqi Wang

    Published 2025-01-01
    “…Then, in the solution process, to address the issues of the Whale Optimization Algorithm (WOA) easily falling into local optima and low convergence accuracy, the BIO-WOA (Bernoulli Chaotic mapping In-nonlinear Factors and Opposition-based Learning Improved Whale Optimization Algorithm, BIO-WOA) is proposed. …”
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  3. 203

    A novel research on network security situation prediction based on iteratively optimized RBF-NN by Yuqin Wu, Congqi Shen, Shungen Xiao, Wei Feng, Yexian Fan, Xiuzhuang Zhou

    Published 2025-05-01
    “…Moreover, we introduce a cross-model method with a genetic algorithm to compute the optimal weights for the RBF-NN model. …”
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    Article
  4. 204

    Optimization of Structural Parameters and Cavitation Suppression in Control Valves Based on P-WOA by W. Li, S. Li, J. Hou, L. Yang, Y. Tian

    Published 2025-06-01
    “…Boosting method integrates reinforcement learning PPO with the whale optimization algorithm (WOA) to form the P-WOA model. …”
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    Article
  5. 205

    A Novel Long Short-Term Memory Seq2Seq Model with Chaos-Based Optimization and Attention Mechanism for Enhanced Dam Deformation Prediction by Lei Wang, Jiajun Wang, Dawei Tong, Xiaoling Wang

    Published 2024-11-01
    “…However, the nonlinear relationships between deformation and time-varying environmental factors pose significant challenges, often limiting the accuracy of conventional and deep learning models. To address these issues, this study aimed to improve the predictive accuracy and interpretability in dam deformation modeling by proposing a novel LSTM seq2seq model that integrates a chaos-based arithmetic optimization algorithm (AOA) and an attention mechanism. …”
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  6. 206
  7. 207

    Subsampling Algorithms for Irregularly Spaced Autoregressive Models by Jiaqi Liu, Ziyang Wang, HaiYing Wang, Nalini Ravishanker

    Published 2024-11-01
    “…The effectiveness of these methods depends on their ability to identify and select data points that improve the estimation efficiency according to some optimality criteria. …”
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  8. 208
  9. 209

    Improved swin transformer-based thorax disease classification with optimal feature selection using chest X-ray. by Nadim Rana, Yahaya Coulibaly, Ayman Noor, Talal H Noor, Md Imran Alam, Zeba Khan, Ali Tahir, Mohammad Zubair Khan

    Published 2025-01-01
    “…To further improve feature selection, we utilize the Chaotic Whale Optimization (ChWO) Algorithm, which optimally selects the most relevant attributes from the extracted features. …”
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    Article
  10. 210

    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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  11. 211
  12. 212

    Primary Frequency Regulation Modeling of Deep Peak Regulation Unit Based on Improved Group Optimization Algorithm by Guoqiang YU, Xiaobo CUI, Yiyue SHI, Keyi TANG, Tianhai ZHANG

    Published 2020-06-01
    “…Then the unknown parameter values in the model are derived by using an improved group optimization algorithm with better global search capability. …”
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  15. 215

    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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  16. 216

    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
  17. 217

    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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  18. 218

    Identifying optimized spectral and spatial features of UAV-based RGB and multispectral images to improve potato nitrogen content estimation by Hang Yin, Haibo Yang, Yuncai Hu, Fei Li, Kang Yu

    Published 2025-12-01
    “…For the combined RGB and MS data, spectral indices were the important input features for the SGPR and VHGPR models. The optimized mND705 was selected as the most critical spectral indices for PNC prediction. …”
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  19. 219

    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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