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    Comprehensive Study of Nonlinear Maglev System Utilizing COOT Optimized FOPID Controller by Marabathina Maheedhar, T. Deepa

    Published 2025-01-01
    “…To improve the performance of the magnetic levitation system, the most recent metaheuristic COOT algorithm was first employed in this study to tune the Fractional Order Proportional Integral and Derivative (FOPID) controller. …”
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    Optimizing production efficiency in semiconductor enterprises by an improve and optimized biogeographical optimization algorithm based on three-layer coding by Jiaqi Liu

    Published 2024-12-01
    “…Propose to use a three-layer coding (TLC) mechanism to improve and optimize the biogeographical optimization algorithm, and use the improved biogeographical optimization (IOBO) algorithm to solve the production efficiency optimization problem of semiconductor enterprises. …”
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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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    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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    Air Quality Prediction Using Neural Networks with Improved Particle Swarm Optimization by Juxiang Zhu, Zhaoliang Zhang, Wei Gu, Chen Zhang, Jinghua Xu, Peng Li

    Published 2025-07-01
    “…Second, the inertia weights and learning factors of the standard PSO are improved to ensure the global search ability exhibited by the algorithm in the early stage and the ability to rapidly obtain the optimal solution in the later stage; we also introduce an adaptive variation algorithm in the particle search process to prevent the particles from being caught in local optima. …”
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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
    “…Finally, an improved ACO (IMACO) algorithm is designed by establishing the natural logarithm function to address the blind search problem in the ACO algorithm. …”
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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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    Enhancing network lifetime in WSNs through coot algorithm-based energy management model by Namita Shinde, Dr. Vinod H․ Patil

    Published 2025-06-01
    “…To improve the performance of Wireless Sensor Networks (WSN), this study offers a novel energy-efficient clustering and routing technique based on the Coot Optimization Algorithm (COA). …”
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    Improved Quantum Artificial Bee Colony Algorithm-Optimized Artificial Intelligence Models for Suspended Sediment Load Predicting by Peng Wei, Wang Yu

    Published 2025-01-01
    “…To evaluate the predictive capability, the models are compared with quantum bee colony algorithm-optimized AI models (QABC-SVR and QABC-ANN), genetic algorithm-optimized AI models (GA-SVR and GA-ANN) and traditional AI models (SVR and ANN). …”
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    Shuffled Puma Optimizer for Parameter Extraction and Sensitivity Analysis in Photovoltaic Models by En-Jui Liu, Rou-Wen Chen, Qing-An Wang, Wan-Ling Lu

    Published 2025-07-01
    “…To address this challenge, a novel metaheuristic algorithm called shuffled puma optimizer (SPO) is deployed to perform parameter extraction and optimal configuration identification across four PV models. …”
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    Bearing Fault Diagnosis Based on Parameter Optimized VMD and ELM with Improved SSA by Yang Sen, Wang Hengdi, Cui Yongcun, Li Chang, Tang Yuanchao

    Published 2023-10-01
    “…Secondly, the improved SSA optimizes the important parameters (decomposition number <italic>K</italic> and penalty factor <italic>α</italic>) of the VMD algorithm, and the fittness function adopts the minimum envelope entropy. …”
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    Improved Monthly Runoff Prediction of OSELM Based on Secondary Decomposition Technique and Optimization of Ten "Bird" Swarm Algorithms by DENG Zhiyu, CUI Dongwen

    Published 2025-01-01
    “…To improve the accuracy of monthly runoff time series prediction and enhance the performance of online sequential extreme learning machine (OSELM) prediction, ten "bird" swarm algorithms were compared and validated for optimization, including satin bowerbird optimizer (SBO)/Harris hawks optimization (HHO)/seagull optimization algorithm (SOA)/African vultures optimization algorithm (AVOA)/coot optimization algorithm (COOT)/pelican optimization algorithm (POA)/eagle perching optimization (EPO)/osprey optimization algorithm (OOA). …”
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    Prediction of Earthquake Death Toll Based on Principal Component Analysis, Improved Whale Optimization Algorithm, and Extreme Gradient Boosting by Chenhui Wang, Xiaotao Zhang, Xiaoshan Wang, Guoping Chang

    Published 2025-08-01
    “…To address the challenges of small sample sizes, high dimensionality, and strong nonlinearity in earthquake fatality prediction, this paper proposes an integrated modeling approach (PCA-IWOA-XGBoost) combining Principal Component Analysis (PCA), the Improved Whale Optimization Algorithm (IWOA), and Extreme Gradient Boosting (XGBoost). …”
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    Unconfined Compressive Strength Prediction of Rocks Using a Novel Hybrid Machine Learning Algorithm by Rafiqul Islam, Md. Arif Hossain

    Published 2024-12-01
    “…This paper introduces a novel methodology for predicting Unconfined Compressive Strength (UCS) in rocks by integrating Support Vector Regression (SVR) with two cutting-edge optimization algorithms: the Seahorse Optimizer (SO) and the COOT Optimization Algorithm (COOT). …”
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