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  1. 1781
  2. 1782

    Optimizing Solid Rocket Missile Trajectories: A Hybrid Approach Using an Evolutionary Algorithm and Machine Learning by Carlo Ferro, Matteo Cafaro, Paolo Maggiore

    Published 2024-11-01
    “…This paper introduces a novel approach for modeling and optimizing the trajectory and behavior of small solid rocket missiles. …”
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    Article
  3. 1783

    Research on multi-objective optimization method for bullet full trajectory based on SA-PSO hybrid algorithm by HU Zhenchao, CUI Xiao, XU Xiao, LU Dabin, ZHANG Huisheng

    Published 2025-08-01
    “…The results demonstrate that this approach converges to the optimal solution more efficiently compared to traditional algorithms. …”
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  4. 1784

    An optimized feature selection using triangle mutation rule and restart strategy in enhanced slime mould algorithm by Ibrahim Musa Conteh, Gibril Njai, Abass Conteh, Qingguo Du

    Published 2025-06-01
    “…This paper proposes an improved feature selection method based on an improved Slime Mould Algorithm (SMA), called the Triangular Mutation Rule Restart Strategy Slime Mould Algorithm (TRSMA), to overcome some of the shortcomings of the SMA, including premature convergence, poor population diversity, and local optima entrapment. …”
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  5. 1785

    Optimal Reactive Power Generation for Radial Distribution Systems Using a Highly Effective Proposed Algorithm by Le Chi Kien, Thuan Thanh Nguyen, Bach Hoang Dinh, Thang Trung Nguyen

    Published 2021-01-01
    “…In this paper, a proposed modified stochastic fractal search algorithm (MSFS) is applied to find the most appropriate site and size of capacitor banks for distribution systems with 33, 69, and 85 buses. …”
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  6. 1786

    Applications of Metaheuristic Algorithms in Solar Air Heater Optimization: A Review of Recent Trends and Future Prospects by Jean De Dieu Niyonteze, Fumin Zou, Godwin Norense Osarumwense Asemota, Walter Nsengiyumva, Noel Hagumimana, Longyun Huang, Aphrodis Nduwamungu, Samuel Bimenyimana

    Published 2021-01-01
    “…Therefore, this paper clearly shows that the use of all six proposed metaheuristic algorithms results in significant efficiency improvements through the selection of the optimal design set and operating parameters for SAHs. …”
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  7. 1787

    A comparative study of the performance of ten metaheuristic algorithms for parameter estimation of solar photovoltaic models by Adel Zga, Farouq Zitouni, Saad Harous, Karam Sallam, Abdulaziz S. Almazyad, Guojiang Xiong, Ali Wagdy Mohamed

    Published 2025-01-01
    “…The Friedman test was utilized to rank the performance of the various algorithms, revealing the Growth Optimizer as the top performer across all the considered models. …”
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  8. 1788

    PCA-FSA-MLR Model and Its Application in Runoff Forecast by GUO Cunwen, CUI Dongwen

    Published 2021-01-01
    “…To improve the accuracy of runoff forecast,and establish a runoff forecast model combining principal component analysis (PCA),future search algorithm (FSA),and multiple linear regression (MLR),this paper reduces the dimensionality of the sample data by PCA,selects 8 standard test functions and simulates and verifies FSA under different dimensional conditions,optimizes MLR constant terms and partial regression coefficients by FSA,proposes a PCA-FSA-MLR runoff forecast model,constructs PCA-LS-MLR,PCA-FSA-SVM,and PCA-SVM models with dimensionality reduction processing by PCA and FSA-MLR,LS-MLR,FSA-SVM,and SVM without dimensionality reduction processing as a comparison model,and verifies each model through forecasting the annual runoff and monthly runoff in December of Longtan station in Yunnan Province.The results show that:①FSA has better optimization accuracy and global extremum search ability under different dimensional conditions;②The average absolute relative error of the annual runoff and monthly runoff in December of Longtan station through PCA-FSA-MLR model are 1.63% and 3.91% respectively,and its forecast accuracy is better than the other 7 models,with higher forecast accuracy and stronger generalization ability;③For the same model,the forecast accuracy after dimensionality reduction processing by PCA is better than that without dimensionality reduction processing,so the data dimensionality reduction by PCA is helpful to improve the forecast accuracy of models.…”
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  9. 1789

    The Optimal Cost Design of Reinforced Concrete Beams Using an Artificial Neural Network—The Effectiveness of Cost-Optimized Training Data by Jaemin So, Seungjae Lee, Jonghyeok Seong, Donwoo Lee

    Published 2025-05-01
    “…This study presents a method for the automated design of reinforced concrete (RC) beam cross-sections using an artificial neural network (ANN) trained with cost-optimized data generated by the crow search algorithm (CSA). …”
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  10. 1790
  11. 1791

    An optimized informer model design for electric vehicle SOC prediction. by Xin Xie, Feng Huang, Yefeng Long, Youyuan Peng, Wenjuan Zhou

    Published 2025-01-01
    “…Therefore, based on the health assessment algorithm, a new optimized Informer model is proposed to predict SOC. …”
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  12. 1792
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    Construction of Graduate Behavior Dynamic Model Based on Dynamic Decision Tree Algorithm by Fen Yang

    Published 2022-01-01
    “…The results show that the big data integration system based on big data and dynamic decision tree algorithm has high adaptability. Incremental adaptive optimization of the traditional decision tree model can significantly improve the prediction effect and prediction time of dynamic data and provide theoretical support for the industrialization and social significance of big data technology. …”
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  15. 1795

    Volute Optimization Based on Self-Adaption Kriging Surrogate Model by Fannian Meng, Ziqi Zhang, Liangwen Wang

    Published 2022-01-01
    “…Optimizing the volute performance can effectively improve the efficiency of a centrifugal fan by changing the volute geometric parameter, so the self-adaption Kriging surrogate model is used to optimize the volute geometric parameter. …”
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  16. 1796
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    Intelligent interference decision algorithm with prior knowledge embedded LSTM-PPO model by ZHANG Jingke, YANG Kai, LI Chao, WANG Hongyan

    Published 2024-12-01
    “…Focusing on the issues of low efficiency and effectiveness in decision-making as well as the instability of traditional reinforcement learning model-based multi-function radar (MFR) jamming decision algorithms, a prior knowledge embedded long short-term memory (LSTM) network-proximal policy optimization (PPO) model based intelligent interference decision algorithm was developed. …”
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  18. 1798
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    Detection of abnormal tourist behavior in scenic spots based on optimized Gaussian model for background modeling by Liu Xiaohua

    Published 2024-11-01
    “…The study proposed a background model constructed by an optimized Gaussian mixture model based on the background subtraction method to eliminate the background interference. …”
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