Showing 641 - 660 results of 726 for search 'Swarm evaluation algorithm', query time: 0.16s Refine Results
  1. 641

    Analysis of power system transient stability with PSO-optimized distributed generation and HVDC transmission systems by Jiyeon Jang, Youngmin Gong, Seunghong Min, Insu Kim

    Published 2025-03-01
    “…The study used a particle swarm optimization (PSO) algorithm to ensure reliable and feasible DG deployment. …”
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    Article
  2. 642

    Optimized CNN-LSTM with hybrid metaheuristic approaches for solar radiation forecasting by İrem Fatma Şener, İhsan Tuğal

    Published 2025-08-01
    “…The performance of several machine learning and deep learning models, including Long Short-Term Memory, Autoregressive Integrated Moving Average, Multilayer Perceptron, Random Forest, XGBoost, Support Vector Regression, and a hybrid CNN-LSTM model, is evaluated for daily solar radiation forecasting. To improve the accuracy of the model, hyperparameter optimization is applied to the CNN-LSTM model using three metaheuristic algorithms: Particle Swarm Optimization, Grey Wolf Optimization, and Starfish Optimization Algorithm. …”
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  3. 643

    A clustering-based co-allocation of battery swapping stations and wind-photovoltaic plants in radial distribution systems by Hamed Shams, Naghi Rostami, Behnam Mohammadi Ivatloo

    Published 2025-07-01
    “…A K-means clustering method is implemented to classify price, energy demand, wind, and photovoltaic generation into appropriate clusters embedded into the particle swarm optimization (PSO) algorithm. The decision variables of PSO are the wind-photovoltaic system capacity and hybrid system placement to supply the EV load demand for battery swapping stations. …”
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  4. 644

    Resilient VPP cost optimization in DER-driven microgrids for large distribution systems considering uncertainty during extreme events by T.D. Suresh, M. Thirumalai, R. Hemalatha, Mohit Bajaj, Vojtech Blazek, Lukas Prokop

    Published 2025-07-01
    “…Simulation results demonstrate the BWO-based strategy’s superior performance, reducing total objective cost to $2.54 million, outperforming genetic algorithm (GA) and particle swarm optimization (PSO) by 5.01% and 8.54% respectively. …”
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  5. 645

    Hyperparameters optimization of evolving spiking neural network using artificial bee colony for unsupervised anomaly detection by Rehan Rabie, Sahran Shahnorbanun, Alyasseri Zaid Abdi Alkareem, Sani Nor Samsiah, Al-Betar Mohammed Azmi

    Published 2025-07-01
    “…Further validation was provided by comparing the proposed OeSNN-ABC against five well-known optimization algorithms: particle swarm optimization, grey wolf optimization, flower pollination algorithm, whale optimization algorithm, and grid search, alongside other classifiers such as random forest, support vector machine, and k-nearest neighbor. …”
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  6. 646

    A Hybrid CNN-LSTM Model With Attention Mechanism for Improved Intrusion Detection in Wireless IoT Sensor Networks by Pendukeni Phalaagae, Adamu Murtala Zungeru, Abid Yahya, Boyce Sigweni, Selvaraj Rajalakshmi

    Published 2025-01-01
    “…To address computational demands, an enhanced Particle Swarm Optimization (PSO) algorithm is implemented for dynamic feature selection, thereby optimizing the system’s efficiency in high-dimensional data environments characteristic of IoT networks. …”
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    Article
  7. 647

    State of charge estimation of lithium-ion batteries in an electric vehicle using hybrid metaheuristic - deep neural networks models by Zuriani Mustaffa, Mohd Herwan Sulaiman, Jeremiah Isuwa

    Published 2025-06-01
    “…These include the barnacle mating optimizer-deep neural networks (BMO-DNNs) with an MAE of 5.3848, an RMSE of 7.0395, and a convergence value of 0.0492; the evolutionary mating algorithm-deep neural networks (EMA-DNNs) with an MAE of 7.6127, an RMSE of 11.2287, and a convergence value of 0.0536; and the particle swarm optimization-deep neural networks (PSO-DNNs) with an MAE of 4.3089, an RMSE of 5.9672, and a convergence value of 0.0345. …”
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    Article
  8. 648

    Integrating Machine Learning Workflow into Numerical Simulation for Optimizing Oil Recovery in Sand-Shale Sequences and Highly Heterogeneous Reservoir by Dung Bui, Abdul-Muaizz Koray, Emmanuel Appiah Kubi, Adewale Amosu, William Ampomah

    Published 2024-10-01
    “…This paper aims to evaluate the efficiency of various machine learning algorithms integrating with numerical simulations in optimizing oil production for a highly heterogeneous reservoir. …”
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  9. 649

    Optimized planning of electric vehicle charging infrastructure for grid performance improvement by Mohammad Reza Maghami, Ka Fei Thang, Arthur G. O. Mutambara, Ali Akbar Firoozi, Elnaz Yaghoubi, Mehdi Zareian Jahromi, Elaheh Yaghoubi

    Published 2025-07-01
    “…This paper presents a multi-objective optimization framework developed using particle swarm optimization (PSO) algorithm to determine optimal placement and capacity of EV charging infrastructures. …”
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    Article
  10. 650

    An Optimal Charging Strategy for PV-Based Battery Swapping Stations in a DC Distribution System by Shengjun Wu, Qingshan Xu, Qun Li, Xiaodong Yuan, Bing Chen

    Published 2017-01-01
    “…Second, three indexes are presented to evaluate operational performance. Then, a particle swarm optimization (PSO) algorithm is developed to calculate the optimal charging power and to minimize the charging cost for each time slot. …”
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    Article
  11. 651

    IoT-enabled real-time health monitoring system for adolescent physical rehabilitation by Jie Yang, Juanjuan Hu, Wenrui Chen

    Published 2025-05-01
    “…Advanced signal processing and filtering techniques are employed to minimize noise interference and improve data accuracy. A particle swarm optimization support vector machine (PSO-SVM) algorithm is utilized to classify motion patterns. …”
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    Article
  12. 652

    Strategic Deployment of a Single Mobile Weather Radar for the Enhancement of Meteorological Observation: A Coverage-Based Location Problem by Bikram Parajuli, Xin Feng

    Published 2025-02-01
    “…The proposed location problem is solved optimally using the geometric branch-and-bound algorithm and heuristically using swarm-based optimization algorithms. …”
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    Article
  13. 653

    Research on adversarial attacks and defense performance of image classification models for automated driving systems by TANG Jun, HUANG Wenjing, LI Shuang, WU Zili

    Published 2025-01-01
    “…Then, sensitivity analyses were carried out across different regions and examples to identify attack mechanisms using three adversarial interpretation algorithms: LRP, Grad-CAM, and LIME. Based on these analysis results, optimization algorithms such as swarm intelligence defense and adversarial training were adopted to verify the classification performance of the model following adversarial training. …”
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  14. 654

    Prediction of compressive strength and characteristics analysis of semi-flexible pavement desert sand grouting material based upon hybrid-BP neural network by Wenbang Zhu, Yuhang Li, Xiumei Zheng, Enze Hao, Dali Zhang, Zhen Wang

    Published 2025-07-01
    “…To precisely obtain DSGM exhibiting exceptional mechanical properties, the Backpropagation Neural Network (BPNN) model was optimized through the utilization of Particle Swarm Optimization (PSO), Sparrow Search Algorithm (SSA), and Genetic Algorithm (GA). …”
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  15. 655

    Control of steering wheel idle jitter based on optimization of engine suspension system with verifications using multi-sensor measurement by Shuilong He, Binqiang Chen, Zhansi Jiang, Yanxue Wang, Fuyun Liu

    Published 2018-06-01
    “…Parameters of the optimized suspension system were obtained by multi-objective particle swarm optimization. Finally, the effectiveness and feasibility of the optimization algorithm to solve the problem of the vehicle’s steering wheel jitter at idle states were verified through a test using multiple acceleration sensors, which has practical values in the engineering field.…”
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  16. 656

    Morlet Wavelet Neural Networks-Based Intelligent Approach to Analyze the Impact of Aligned Magnetic Field on a Nanofluid Thin Film Flow With Irreversibility Analysis and Chemical R... by Muhammad Ramzan, Xiangning Zhou, Abdulkafi Mohammed Saeed, C. Ahamed Saleel, Ibtehal Alazman, W. S. Koh, Seifedine Kadry

    Published 2025-01-01
    “…The MW function transforms the ODEs into an artificial NNs-based fitness function and then particle swarm optimization (PSO) is used for optimal fitness values. …”
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    Article
  17. 657

    A New Framework for Dynamic Educational Marketing Segmentation in Student Recruitment: Optimizing Fuzzy C-Means with Metaheuristic Techniques by Rizal Bakri, Bobur Sobirov, Niken Probondani Astuti, Ansari Saleh Ahmar, Pawan Kumar Singh

    Published 2025-06-01
    “…This study develops a new framework for dynamic educational marketing segmentation in student recruitment by optimizing FCM using three metaheuristic techniques: Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Differential Evolution (DE). …”
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  18. 658

    Robust collaborative mesh networking with large-scale distributed wireless heterogeneous terminals in industrial cyber-physical systems by Tao Wang, Jun Liu, Lianglun Cheng, Hong Xiao

    Published 2017-09-01
    “…Second, the robustness-aware collaborative mesh networking problem is formulated with a multi-objective optimization model, and an improved multi-objective particle swarm optimization algorithm based on self-adaptive evolutionary learning is exploited to search out the Pareto optimal particles with better distribution and diversity. …”
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    Article
  19. 659

    A Review of the Performance of Smart Lawnmower Development: Theoretical and Practical Implications by Elwin Nesan Selvanesan, Kia Wai Liew, Chai Hua Tay, Jian Ai Yeow, Yu Jin Ng, Peng Lean Chong, Chun Quan Kang

    Published 2025-05-01
    “…Smart lawnmowers have been found to contribute to advancements in machine learning algorithms and possibly swarm robotics. Environmental benefits, such as reduced emissions and noise pollution, were also highlighted in this review. …”
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    Article
  20. 660

    Structural integrity and hybrid ANFIS-PSO modeling of the corrosion rate of ductile irons in different environments by Ukoba K., Akinribide O.J., Adeleke O.

    Published 2024-07-01
    “…The experimental results from this study were used to validate a model generated from hybrid adaptive neuro-fuzzy inferences system-particle swarm optimization (ANFIS-PSO) algorithms. The hybrid ANFIS-PSO modelling technique was improvised for a detailed evaluation of corrosion rate of ductile cast iron materials in different environments. …”
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    Article