Showing 1 - 20 results of 1,114 for search '(improved OR improve) ((most OR root) OR post) optimization algorithm', query time: 0.23s Refine Results
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    Apllication of optimization algorithms to improve the design of turnouts by B. E. Glyuzberg

    Published 2016-04-01
    “…One of the most important tasks for improving the infrastructure facility of railways is its optimization. …”
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    Designing a new optimal controller for a PEMFC by an improved design of the Coot Optimizer by Zheng Wang, Mehrdad Rezaie, Gholamreza Fathi

    Published 2025-05-01
    “…Comparative analyses against three other control techniques confirm a wide system enhancement, evidenced by a substantial reduction in both current and overshoot ripples. Algorithm verification using benchmark functions shows the ICOA achieves lower mean values and standard deviations, with p-values indicating statistically significant improvements (p < 0.05) in Root Mean Square Error (RMSE) compared to COA, MVO, EPO, and LOA algorithms, validating its enhanced optimization capabilities for PEMFC control.…”
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    Design of efficient generalized digital fractional order differentiators using an improved whale optimization algorithm by Mohammed Ali Mohammed Moqbel, Talal Ahmed Ali Ali, Zhu Xiao, Amani Ali Ahmed Ali

    Published 2025-07-01
    “…The proposed method utilizes an improved whale optimization algorithm (IWOA) to compute the optimal coefficients of IIR subfilters of the realization structure. …”
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    Research on Robot Path Planning Based on Improved RRT-Connect Algorithm by CHEN Zhilan, TANG Haoyang

    Published 2025-02-01
    “…Firstly, an improved RRT algorithm is employed to search and add a middle root node, facilitating the simultaneous expansion of four random trees to expedite algorithm convergence. …”
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    Congestion Management Using an Optimized Deep Convolution Neural Network in Deregulated Environment by Dhanadeepika B., Vanithasri M., Chakravarthi M.

    Published 2023-08-01
    “…This analysis incorporates restrictions such as line loads, bus voltage influence, generator, line limits, etc. The most important results for the test system indicating convergence profile, congestion cost, and change in real-power and voltage magnitude are obtained by the simulation in MATLAB, and on the basis of the obtained simulation outcomes, it is evident that the proposed Improved Lion Algorithm optimized Deep Convolution Neural Network displays phenomenal computation performance in minimizing congestion losses at minimum congestion costs. …”
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    Environmental Impact Minimization Model for Storage Yard of In-Situ Produced PC Components: Comparison of Dung Beetle Algorithm and Improved Dung Beetle Algorithm by Jeeyoung Lim, Sunkuk Kim

    Published 2024-11-01
    “…As a result of applying the developed model, the optimization of the improved dung beetle optimization algorithm was verified to be efficient by improving the neighboring correlation by 22.79% and reducing carbon dioxide emissions by 18.33% compared to the dung beetle optimization algorithm. …”
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    An improved Multi-Objective Whale Optimization Algorithm for hydrodynamic and acoustic performance optimization of Myring-shaped underwater vehicle by Qigan Wang, Yu Dong, Han Wu, Peizhan Cao, Zhijun Zhang

    Published 2025-12-01
    “…These improvements enhance the algorithm’s capability in solving Multi-Objective Optimization (MOP) problems. …”
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    Improving Airport Flight Prediction System Based on Optimized Regression Vector Machine Algorithm by Baraa Yousif Salman, Jaber Parchami

    Published 2024-09-01
    “…In this research, the optimized support vector regression (SVR) algorithm has been used to improve the accuracy of air delay prediction. …”
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    Improved Monarch Butterfly Optimization Algorithm Based on Opposition-Based Learning and Random Local Perturbation by Lin Sun, Suisui Chen, Jiucheng Xu, Yun Tian

    Published 2019-01-01
    “…Many optimization problems have become increasingly complex, which promotes researches on the improvement of different optimization algorithms. …”
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    Enhanced Dung Beetle Optimizer-Optimized KELM for Pile Bearing Capacity Prediction by Bohang Chen, Mingwei Hai, Gaojian Di, Bin Zhou, Qi Zhang, Miao Wang, Yanxiu Guo

    Published 2025-07-01
    “…In response to the need for rapid and precise predictions of pile bearing capacity, this study introduces a kernel extreme learning machine (KELM) prediction model optimized through a multi-strategy improved beetle optimization algorithm (IDBO), referred to as the IDBO-KELM model. …”
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    Application of bioinspired global optimization algorithms to the improvement of the prediction accuracy of compact extreme learning machines by L. A. Demidova, A. V. Gorchakov

    Published 2022-04-01
    “…By adjusting input weights with bioinspired optimization algorithms, it was shown that the prediction accuracy of ELMs in regression problems can be improved to reduce the number of hidden-layer neurons to reach a high prediction accuracy on learning and test datasets. …”
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    Structural Simulation Model Updating Based on Improved MCMC Algorithm and Surrogate Model by MIAO Ji, DUAN Liping, LIU Jiming, LIN Siwei, ZHAO Jincheng

    Published 2025-08-01
    “…The results show that WOA can significantly improve the stability and convergence speed of the MCMC algorithm, the updating efficiency can be improved by 13.9% at most, and the maximum frequency errors of the simply supported beam model and the three-story steel frame model updated by the WO-MH algorithm are 0.009% and 2.41%, respectively. …”
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    Coal Price Forecasting Using CEEMDAN Decomposition and IFOA-Optimized LSTM Model by Zhuang Liu, Xiaotuan Li

    Published 2025-07-01
    “…Abstract This study introduces a novel hybrid forecasting model for coking coal prices, integrating complete ensemble empirical mode decomposition with adaptive noise (CEEMDAN) and long short-term memory (LSTM) neural networks, enhanced by an improved fruit fly optimization algorithm (IFOA). The approach begins with CEEMDAN decomposing the coking coal price sequence into intrinsic mode functions (IMFs) and a residual component, effectively mitigating non-stationarity and nonlinearity. …”
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    An Adaptive Fusion Path Tracking Strategy for Autonomous Vehicles Based on Improved ACO Algorithm by Jihan Zhang, Yuan Wang, Jinyan Hu, Hongwu You

    Published 2025-01-01
    “…Although methods based on dynamic models and optimization theory can improve tracking performance, most autonomous systems lack high-fidelity models and the complexity of optimization processes lead to increase computational burden. …”
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