Showing 61 - 80 results of 110 for search 'Swarm evaluation algorithm', query time: 0.07s Refine Results
  1. 61

    Optimizing enhanced coalbed methane recovery in thick lignite formations: An integrated technical and economic evaluation by Zhiming Fang, Shaicheng Shen

    Published 2025-09-01
    “…We evaluate the economic feasibility of ECBM under various gas injection scenarios and optimize key operational parameters through a coupled neural network model and particle swarm optimization algorithm. …”
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    Article
  2. 62

    Optimisation of Aluminium Alloy Variable Diameter Tubes Hydroforming Process Based on Machine Learning by Yong Xu, Xuewei Zhang, Wenlong Xie, Shihong Zhang, Yaqiang Tian, Liansheng Chen

    Published 2025-05-01
    “…To predict the forming behaviour of aluminium alloy variable diameter tubes during hydroforming, a genetic algorithm-enhanced particle swarm optimisation (GA-PSO) is used to optimise a backpropagation neural network (BP-NN). …”
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  3. 63

    Coverage optimization of wireless sensor network utilizing an improved CS with multi-strategies by Sen-Yu Yang, Chang-Feng Chen, Kai-Qing Zhou, Yun Ou

    Published 2025-08-01
    “…Cuckoo Search (CS), as a type of Swarm Intelligence (SI) algorithm, has garnered significant attention from researchers due to its strong global search capability enabled by the Lévy flight mechanism. …”
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  4. 64

    Hybrid extreme learning machine for real-time rate of penetration prediction by Abdelhamid Kenioua, Omar Djebili, Ammar Touati Brahim

    Published 2025-08-01
    “…Abstract This study presents a comparative analysis of hybrid Extreme Learning Machine (ELM) models optimized with metaheuristic algorithms Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Whale Optimization Algorithm (WOA), and Grey Wolf Optimizer (GWO) for real-time Rate of Penetration (ROP) prediction in drilling operations. …”
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    Article
  5. 65

    College psychological stress assessment system based on LabVIEW and WTA integration by Ting Wang

    Published 2025-12-01
    “…The system collects and analyzes electrocardiogram signals of students in different psychological states, and uses Back Propagation neural networks and particle swarm optimization algorithms to evaluate the level of psychological stress. …”
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    Article
  6. 66

    Hybrid Metaheuristic Optimization of HVAC Energy Consumption and Thermal Comfort in an Office Building Using EnergyPlus by Reza Akraminejad, Tianyi Zhao, Yacine Rezgui, Ali Ghoroghi, Yousef Shahbazi Razlighi

    Published 2025-07-01
    “…Following correlation analyses to understand parameter relationships, we implement our hybrid multi-objective approach. Comparative evaluations against state-of-the-art algorithms, including MoPso, NSGA-II, hybrid Nsga2/MOEAD, and Mo-CSA, validated the effectiveness of HCRPN. …”
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  7. 67

    Integrated decision support system for optimizing time and cost trade offs in linear repetitive construction projects by Ahmed Gouda Mohamed, Ali Hassan Ali, Ahmed Adel Abdelhady

    Published 2025-06-01
    “…Unlike previous studies that focus solely on single-algorithm applications, this research evaluates two metaheuristic optimization strategies—Genetic Algorithm (GA) and Particle Swarm Optimization (PSO)—within a consistent problem setting. …”
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  8. 68

    Adaptive Multi-Objective Firefly Optimization for Energy-Efficient and QoS-Aware Scheduling in Distributed Green Data Centers by Ahmed Chiheb Ammari, Wael Labidi, Rami Al-Hmouz

    Published 2025-06-01
    “…AFBO is evaluated using real-world trace-driven simulations and compared against benchmark multi-objective algorithms, including multi-objective particle swarm optimization (MOPSO), simulated annealing-based bi-objective differential evolution (SBDE), and the baseline Multi-Objective Firefly Algorithm (MOFA). …”
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  9. 69

    Exploration and Exploitation Mechanism in Pairwise Test Case Generation: A Systematic Literature Review by Muhammad Sabo Yahaya, Ahmad Sobri B. Hashim, Abdullateef Oluwagbemiga Balogun, Aminu Aminu Muazu, Fatima Sabo Usman, Dahiru Adamu Aliyu, Abdullahi Uwaisu Muhammad

    Published 2025-01-01
    “…Covering research from 2014 to 2024, the review evaluates hybrid and metaheuristic strategies, including Pairwise Migrating Birds Optimization-Based Strategies (PMBOS), Pairwise Gravitational Search Algorithm Strategy (PGSAS), Pairwise hybrid Artificial Bee Colony (PhABC), Genetic and Particle Swarm Optimization (GAPSO) algorithm, Hybrid Optimization Algorithm (HOA), and Parameter Free Choice Function based Hyper-Heuristic (PCFHH), among others. …”
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    Article
  10. 70

    A novel global MPPT method based on sooty tern optimization for photovoltaic systems under complex partial shading by Mohammed Taha Kaaitan, Rashid Ali Fayadh, Zuhair S. AL-sagar, Salam J. Yaqoob, Mohit Bajaj, Mebratu Sintie Geremew

    Published 2025-07-01
    “…A comprehensive simulation framework was implemented in MATLAB/Simulink, employing a 3 × 3 PV array (3 kW capacity) and a boost converter to test the proposed method across four shading scenarios, including highly irregular and dynamic patterns. Performance evaluation against benchmark algorithms—Perturb & Observe (P&O), Particle Swarm Optimization (PSO), and Grey Wolf Optimization (GWO)—revealed that STOA consistently outperformed its counterparts. …”
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  11. 71

    Development of A Novel Discharge Routing Method Based On the Large Discharge Dataset, Muskingum Model, Optimization Methods, and Multi-Criteria Decision Making by Mahdi Valikhan Anaraki, Saeed Farzin, Iman Ahmadianfar, Amin Shams

    Published 2024-10-01
    “…Different MOAs, including a Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Firefly Algorithm (FFA), Cuckoo Search (CS), Bat Algorithm (BA), Shark Smell Optimization (SSO), Whale Optimization Algorithm (WOA), Harris Hawk''s Optimization (HHO), and hybrid of WOA and CS (WOA_CS), were developed for Muskingum calibration. …”
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    Article
  12. 72

    Machine Learning and Metaheuristics Approach for Individual Credit Risk Assessment: A Systematic Literature Review by Álex Paz, Broderick Crawford, Eric Monfroy, José Barrera-García, Álvaro Peña Fritz, Ricardo Soto, Felipe Cisternas-Caneo, Andrés Yáñez

    Published 2025-05-01
    “…It categorizes the use of machine learning algorithms, feature selection methods, and metaheuristic optimization techniques, including genetic algorithms, particle swarm optimization, and biogeography-based optimization. …”
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    Article
  13. 73

    A survey on autonomous navigation for mobile robots: From traditional techniques to deep learning and large language models by Abderrahim Waga, Said Benhlima, Ali Bekri, Jawad Abdouni, Fatima Zahrae Saber

    Published 2025-08-01
    “…The review extends to modern metaheuristic algorithms, including genetic algorithms (GA), particle swarm optimization (PSO), and ant colony optimization (ACO). …”
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  14. 74

    Classification Prediction of Rockburst in Railway Tunnel Based on Hybrid PSO-BP Neural Network by Min Zhang

    Published 2022-01-01
    “…In order to accurately predict the rockburst intensity level of the railway tunnel, the rock stress coefficient σθ/σc, rock brittleness coefficient σc/σt, and elastic energy index Wet are used as evaluation indexes of rockburst intensity, and a BP neural network rockburst prediction model based on hybrid particle swarm optimization algorithm is proposed. …”
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  15. 75

    An Effective ABC-SVM Approach for Surface Roughness Prediction in Manufacturing Processes by Juan Lu, Xiaoping Liao, Steven Li, Haibin Ouyang, Kai Chen, Bing Huang

    Published 2019-01-01
    “…Further, to evaluate the optimization performance of ABC in parameters determination of SVM, this study compares the prediction performance of SVM models optimized by well-known evolutionary and swarm-based algorithms (differential evolution (DE), genetic algorithm (GA), particle swarm optimization (PSO), and ABC) and analyzes ability of these optimization algorithms from their optimization mechanism and convergence speed based on experimental datasets of turning and milling. …”
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  16. 76

    Gaussian barebone mechanism and wormhole strategy enhanced moth flame optimization for global optimization and medical diagnostics. by Jingjing Ma, Zhifang Zhao, Lin Zhang

    Published 2025-01-01
    “…Moth Flame Optimization (MFO) is a swarm intelligence algorithm inspired by the nocturnal flight mode of moths, and it has been widely used in various fields due to its simple structure and high optimization efficiency. …”
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  17. 77

    Enhancing education quality with hybrid clustering and evolutionary neural networks in a multi phase framework by Saleem Malik, Chandrakanta Mahanty, Jnanaranjan Mohanty, Krunal Vaghela, T. Narmadha, R. Sivaranjani, Javed Khan Bhutto, Saiful Islam, Anwar Khan, Amanuel Zewdie

    Published 2025-07-01
    “…The NeuroEvoClass algorithm mixes evolutionary strategies inspired by swarm intelligence and artificial neural networks (ANN) to improve student performance prediction in Phase II. …”
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    Article
  18. 78

    Blasting vibration velocity prediction of open pit mines based on GRA-EPSO-SVM model by Pengfei ZHANG, Yong YUAN, Yunhua HE, Shaojun DAI, Jiazhen LI, Xuehai CHI, Wei LI, Xue SUN, Jiao ZHANG, Runcai BAI, Honglu FEI

    Published 2025-07-01
    “…The peak value of blasting vibration in open pit mine is the main index to evaluate blasting effect. In the scene of coal and rock interbedded blasting in open-pit mine, aiming at the problems that the existing prediction methods of blasting vibration peak value are difficult to achieve ideal prediction results, resulting in unreasonable design of blasting parameters and initiation network, a prediction model of blasting vibration peak value based on integrated particle swarm optimization support vector machine algorithm (GRA-EPSO-SVM) with grey correlation degree feature selection is proposed. …”
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    Article
  19. 79

    Neuro-evolutionary models for imbalanced classification problems by Israa Al-Badarneh, Maria Habib, Ibrahim Aljarah, Hossam Faris

    Published 2022-06-01
    “…The utilized algorithms are the Grey Wolf Optimization (GWO), Particle Swarm Optimization (PSO), and the Salp Swarm Algorithm (SSA). …”
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    Article
  20. 80

    Weak fault diagnosis method for rolling bearings under strong background noise based on EEMD-FK-AMCKD by XIE Guizhong, XU Shuaiqiang, DU Wenliao, LUO Shuangqiang, LI Hao, WANG Liangwen, GONG Xiaoyun

    Published 2025-08-01
    “…Subsequently, particle swarm optimization (PSO) was utilized to adaptively determine the MCKD parameters, and the AMCKD algorithm was applied to enhance the features of the filtered signal. …”
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