Showing 1,221 - 1,240 results of 8,683 for search 'optimal computing algorithms', query time: 0.20s Refine Results
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    Parameter identification of sound absorption model of porous materials based on modified particle swarm optimization algorithm. by Xiaomei Xu, Ping Lin

    Published 2021-01-01
    “…In the aspect of computer running time, compared with the standard particle swarm optimization algorithm, the modified particle swarm optimization algorithm takes shorter running time. …”
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    ACIVY: An Enhanced IVY Optimization Algorithm with Adaptive Cross Strategies for Complex Engineering Design and UAV Navigation by Heming Jia, Mahmoud Abdel-salam, Gang Hu

    Published 2025-07-01
    “…The algorithm’s exceptional convergence precision, solution reliability, and computational efficiency establish it as a powerful tool for challenging optimization problems requiring both accuracy and consistency.…”
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  7. 1227

    A Hybrid ARO Algorithm and Key Point Retention Strategy Trajectory Optimization for UAV Path Planning by Bei Liu, Yuefeng Cai, Duantengchuan Li, Ke Lin, Guanghui Xu

    Published 2024-11-01
    “…However, existing path planning algorithms often encounter problems such as high computational costs and a tendency to become trapped in local optima in complex 3D environments with multiple constraints. …”
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    Optimizing water purification in double slope solar stills using abc algorithm and machine learning techniques by Mcluret, S. Joe Patrick Gnanaraj

    Published 2025-04-01
    “…In this era of intelligent optimization, this study integrates metaheuristic algorithms, computational intelligence, and statistical modeling to enhance performance. …”
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    Optimization of Bolted Steel T-Stub Connection Based on Nonlinear Finite Element Analysis Using Genetic Algorithm by Péter Grubits, Tamás Balogh, Majid Movahedi Rad

    Published 2025-01-01
    “…However, steel connections remain inherently complex due to nonlinear behavior, cost considerations, and code compliance, framing the design process as a discrete structural optimization problem. This research addresses these challenges by presenting a comprehensive calculation framework that combines the finite element method (FEM) and genetic algorithm (GA) to accurately evaluate the structural performance of bolted T-stub configurations. …”
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    Analysis of War Optimization Algorithm in a Multi-Loop Power System Based on Directional Overcurrent Relays by Bakht Muhammad Khan, Abdul Wadood, Shahbaz Khan, Husan Ali, Tahir Khurshaid, Asim Iqbal, Ki Chai Kim

    Published 2024-11-01
    “…The optimization problem is addressed by adjusting the time multiplier setting (TMS) using the War Strategy Optimization (WSO) algorithm, which efficiently solves this constrained problem. …”
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    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
    “…Following trajectory optimization, the derived data are used to train an ML model that predicts setup parameters, significantly reducing computational costs and time. …”
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    AGV Scheduling and Energy Consumption Optimization in Automated Container Terminals Based on Variable Neighborhood Search Algorithm by Ning Zhao, Rongao Li, Xiaoming Yang

    Published 2025-03-01
    “…Finally, the influence of the number and speed of AGVs on the total energy consumption is discussed, and the optimization performance of the variable neighborhood search algorithm and genetic algorithm is compared through computational experiments. …”
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    Effect of the Sampling of a Dataset in the Hyperparameter Optimization Phase over the Efficiency of a Machine Learning Algorithm by Noemí DeCastro-García, Ángel Luis Muñoz Castañeda, David Escudero García, Miguel V. Carriegos

    Published 2019-01-01
    “…Since one of the most critical aspects in this computational consume is the available dataset, among others, in this paper we perform a study of the effect of using different partitions of a dataset in the hyperparameter optimization phase over the efficiency of a Machine Learning algorithm. …”
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