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  1. 21

    A model adapted to predict blast vibration velocity at complex sites: An artificial neural network improved by the grasshopper optimization algorithm by Yong Fan, Guangdong Yang, Yong Pei, Xianze Cui, Bin Tian

    Published 2025-06-01
    “…Through a comprehensive evaluation of the running time results, the root mean square error (RMSE), mean absolute error (MAE), and determination coefficient (R2), a new algorithm, the grasshopper optimization algorithm (GOA), which is suitable for optimizing an ANN to predict PPV, is obtained. …”
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  2. 22

    Comprehensive recognition algorithm of RS code based on fast code root trial by Xiaolin ZHANG, Xiuqiao LI, Rongchen SUN

    Published 2022-11-01
    “…In order to solve the problem of high computation and high missed alarm probability of RS (Reed-Solomon) codes for recognition, comprehensive recognition algorithm of RS codes based on fast code root trial was proposed.Firstly, the check relationship was solved in binary equivalently and fast code root trial was used to check parameters in sequence.Secondly, according to distribution characteristics of the combined code roots, m-level primitive polynomial field and error correction ability was associatively determined.Finally, the short codes and long codes were given different confidence weights and the determined parameters were comprehensively analyzed.The optimal parameter was selected and the generate polynomial was calculated.The proposed algorithm did not need prior information such as signal-to-noise ratio (SNR), and had good adaptability.The simulation results show that the proposed algorithm can effectively reduce the missed alarm probability under the condition of low complexity.Compared with the conventional hard decision algorithm, the performance of the proposed algorithm is improved, and the parameter recognition of RS codes can be completed quickly.…”
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    Research on a hybrid deep learning model based on two-stage decomposition and an improved whale optimization algorithm for air quality index prediction by Hangyu Zhou, Yongquan Yan

    Published 2025-12-01
    “…The model's hyperparameters are optimized by the Improved Whale Optimization Algorithm (IWOA), which improves search efficacy by including chaotic mapping, a nonlinear shrinkage factor, and a Levy flight strategy. …”
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    Vortex-Induced Vibration Performance Prediction of Double-Deck Steel Truss Bridge Based on Improved Machine Learning Algorithm by Yang Yang, Huiwen Hou, Gang Yao, Bo Wu

    Published 2025-04-01
    “…To predict the VIV performance of a double-deck steel truss (DDST) girder with additional aerodynamic measures, the VIV response of a DDST bridge was investigated using wind tunnel tests and numerical simulation, a learning sample database was established with numerical simulation results, and a prediction model for the amplitude of the DDST girder and VIV parameters was established based on three machine learning algorithms. The optimization algorithm was selected using root mean square error (RMSE) and the coefficient of determination (R<sup>2</sup>) as evaluation indices and further improved with a genetic algorithm and particle swarm optimization. …”
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  7. 27

    Safety Status Prediction Model of Transmission Tower Based on Improved Coati Optimization-Based Support Vector Machine by Xinxi Gong, Yaozhong Zhu, Yanhai Wang, Enyang Li, Yuhao Zhang, Zilong Zhang

    Published 2024-11-01
    “…This paper presents a safety state prediction model for transmission towers utilizing improved coati optimization-based SVM (ICOA-SVM). Initially, we optimize the coati optimization algorithm (COA) through inverse refraction learning and Levy flight strategy. …”
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  8. 28

    Path Planning of Intelligent Mobile Robots with an Improved RRT Algorithm by Wenliang Zhu, Guanming Qiu

    Published 2025-03-01
    “…Addressing issues such as pronounced randomness, low search efficiency, inefficient utilization of effective points, suboptimal path smoothness, and potential deviations from the optimal path in the RRT algorithm based on random sampling, we proposed an optimization algorithm that integrates Kalman filtering to eliminate redundant points along the path. …”
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    Residual Life Prediction of Proton Exchange Membrane Fuel Cell Based on Improved ESN by Tiejiang YUAN, Rongsheng LI, Jiandong KANG, Huaguang YAN

    Published 2025-05-01
    “…Aiming at the problem that the current residual effective life prediction (RUL) technique for proton exchange membrane fuel cells (PEMFCs) has poor prediction effect in the medium and long term, a residual life prediction method based on the Improved Gray Wolf Optimization algorithm (IGWO) and Echo State Network (ESN) is proposed, in which the voltage of the electric stack is firstly selected as a health indicator, and the PEMFC dataset is processed by using convolutional smoothing filtering method to carry out data Smoothing and normalization are used to effectively reduce the interference of outliers on the subsequent model training. …”
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  11. 31

    (IoT) Network intrusion detection system using optimization algorithms by Luo Shan

    Published 2025-07-01
    “…Abstract To address the complex requirements of network intrusion detection in IoT environments, this study proposes a hybrid intelligent framework that integrates the Whale Optimization Algorithm (WOA) and the Grey Wolf Optimization (GWO) algorithm—referred to as WOA-GWO. …”
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    Novel nonlinear wind power prediction based on improved iterative algorithm by Fu Zhen-yu, Lin Gui-quan, Tian Wei-da, Pan Zhi-hao, Zhang Wei-cong

    Published 2025-12-01
    “…To effectively improve the accuracy of wind power prediction and reduce the load on the power grid, a new nonlinear wind power prediction model based on an improved iterative learning algorithm was investigated. …”
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  14. 34

    An Improved Shuffled Frog Leaping Algorithm for Electrical Resistivity Tomography Inversion by Fuyu Jiang, Likun Gao, Run Han, Minghui Dai, Haijun Chen, Jiong Ni, Yao Lei, Xiaoyu Xu, Sheng Zhang

    Published 2025-07-01
    “…Second, an adaptive movement operator is constructed to dynamically regulate the step size of the search, enhancing the guiding effect of the optimal solution. In synthetic data tests of three typical electrical models, including a high-resistivity anomaly with 5% random noise, a normal fault, and a reverse fault, the improved algorithm shows an approximately 2.3 times higher accuracy in boundary identification of the anomaly body compared to the least squares (LS) method and standard SFLA. …”
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  15. 35

    Loss reduction optimization strategies for medium and low-voltage distribution networks based on Intelligent optimization algorithms by Nian Liu, Yuehan Zhao

    Published 2024-11-01
    “…Methodology In order to reduce line losses, a loss optimization model for low and medium voltage distribution networks based on an improved Gray Wolf optimization support vector machine is proposed. …”
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  16. 36

    Continuous prediction of knee joint angle in lower limbs based on sEMG: a method combining an improved ZOA optimizer and attention-enhanced GRU by Jian Lv, Binhao Huang, Ligang Qiang

    Published 2025-07-01
    “…Experimental evaluations across three motion tasks—level walking, stair ascent, and stair descent—demonstrated that the proposed method achieved a minimum root mean square error (RMSE) of 1.31°, with over 50% reduction in feature dimensionality, significantly outperforming Genetic Algorithm (GA), Zebra Optimization Algorithm (ZOA), Liver Cancer Algorithm (LCA), and Pied Kingfisher Optimizer (PKO). …”
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  17. 37

    Improved artificial protozoa optimizer: A new method for solar photovoltaic parameter estimation by Wenhao Lai, Duoduo Liu, Jialong Yang, Lei Guo, Weijin Qian, Jiaojiao Wu, Haifeng Zhou

    Published 2025-09-01
    “…We propose an improved Artificial Protozoa Optimizer (iAPO) algorithm for the parameter estimation of photovoltaic cells. …”
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    Control Optimization of Stochastic Systems Based on Adaptive Correction CKF Algorithm by FengJun Hu, Qian Zhang, Gang Wu

    Published 2020-01-01
    “…The control model is established by using the CKF algorithm, the covariance matrix of standard CKF is optimized by square root filter, the adaptive correction of error covariance matrix is realized by adding memory factor to the filter, and the disturbance factors in nonlinear time-varying discrete stochastic systems are eliminated by multistep feedback predictive control strategy, so as to improve the robustness of the algorithm. …”
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