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  1. 2001

    Application Research of Key Frames Extraction Technology Combined with Optimized Faster R-CNN Algorithm in Traffic Video Analysis by Zhi-guang Jiang, Xiao-tian Shi

    Published 2021-01-01
    “…The experimental results show that the key frame extraction technology combined with the optimized Faster R-CNN algorithm model greatly improves the accuracy of detection and reduces the leakage. …”
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    Article
  2. 2002

    Hyperparameter Optimization for Problem-Based Custom CNN Architectures Using a Smart Grid Search Method by H. Aktas

    Published 2025-01-01
    “…To classify the ripe and unripe pistachios with a small-sized and high test accuracy model, a two-layer CNN architecture’s hyperparameters were optimized with the proposed algorithm. …”
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    Article
  3. 2003

    Balancing conflicting objectives in pre-salt reservoir development: A robust multi-objective optimization framework by Auref Rostamian, Amir Davari Malekabadi, Marx Vladimir De Souda Miranda, Vinicius Edurado Botechia, Denis José Schiozer

    Published 2025-01-01
    “…The study focuses on maximizing expected monetary value (EMV) and the net present value of RM4 considering economic uncertainty (NPVeco of RM4), of the most pessimistic scenario among the RMs. The optimization variables are location, type (injection or production), and number of wells, while the non-dominated sorting genetic algorithm II (NSGA-II) is employed for multi-objective optimization. …”
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    Article
  4. 2004

    Prediction of chloride concentration in concrete under multi-salt environment: Optimization of integrated algorithm based on MSCPO and interpretability analysis by Daming Luo, Kanglei Du, Ditao Niu

    Published 2025-03-01
    “…The Improved Mixture Self-Adaptation Crested Porcupine Optimizer (MSCPO) optimized hyperparameters for XGBoost, LightGBM, and Catboost models separately. …”
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    Article
  5. 2005

    Enhanced ANN-Based MPPT for Photovoltaic Systems: Integrating Metaheuristic and Analytical Algorithms for Optimal Performance Under Partial Shading by Alpaslan Demirci, Idriss Dagal, Said Mirza Tercan, Hasan Gundogdu, Musa Terkes, Umit Cali

    Published 2025-01-01
    “…The results demonstrate that the improved ANN-based MPPT algorithm consistently outperforms existing MPPT techniques, including the Perturb and Observe (P&O) and Grey Wolf Optimization (GWO), Harris Hawks Optimization (HHO), and Particle Swarm Optimization (PSO) methods. …”
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    Article
  6. 2006

    An Improved Particle Swarm Optimization and Adaptive Neuro-Fuzzy Inference System for Predicting the Energy Consumption of University Residence by Stephen Oladipo, Yanxia Sun, Oluwatobi Adeleke

    Published 2023-01-01
    “…Following that, the modified PSO (MPSO) is used to optimize the ANFIS parameters for the best model prediction. …”
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    Article
  7. 2007

    Integrated energy microgrids participating in voltage regulation ancillary services: An improved ADMM based distributed optimization approach by Hao Xiao, Wei Pei, Daoxin Han, Xiaowei Pu, Jiarui Wang

    Published 2024-12-01
    “…Moreover, an improved accelerated consensus alternating direction method of multipliers algorithm is proposed to accelerate distributed optimization solutions of the model while protecting user privacy. …”
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    Article
  8. 2008
  9. 2009

    Numerical Design Structure Matrix–Genetic Algorithm-Based Optimization Method for Design Process of Complex Civil Aircraft Systems by Qiucen Fan, Yanlong Han, An Zhang, Wenhao Bi

    Published 2024-12-01
    “…The algorithm NSGA-II is improved and verified with the flight control system design as a case study. …”
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    Article
  10. 2010

    Explainable AI-Based Skin Cancer Detection Using CNN, Particle Swarm Optimization and Machine Learning by Syed Adil Hussain Shah, Syed Taimoor Hussain Shah, Roa’a Khaled, Andrea Buccoliero, Syed Baqir Hussain Shah, Angelo Di Terlizzi, Giacomo Di Benedetto, Marco Agostino Deriu

    Published 2024-12-01
    “…To address these limitations, this study proposes a comprehensive pipeline combining transfer learning, feature selection, and machine-learning algorithms to improve detection accuracy. Multiple pretrained CNN models were evaluated, with Xception emerging as the optimal choice for its balance of computational efficiency and performance. …”
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    Article
  11. 2011
  12. 2012

    State of Health Prediction for Lithium-Ion Batteries Based on Gated Temporal Network Assisted by Improved Grasshopper Optimization by Xiankun Wei, Silun Peng, Mingli Mo

    Published 2025-07-01
    “…The experimental results demonstrate that the proposed IGOA-GGNN-TCN framework offers a novel and effective approach for state-of-health (SOH) estimation in lithium-ion batteries. By integrating improved grasshopper optimization (IGOA) with hybrid graph-temporal modeling, the method achieves superior prediction accuracy compared to conventional techniques, providing a promising tool for battery management systems in real-world applications.…”
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    Article
  13. 2013

    Noise Elimination for Wide Field Electromagnetic Data via Improved Dung Beetle Optimized Gated Recurrent Unit by Zhongyuan Liu, Xian Zhang, Diquan Li, Shupeng Liu, Ke Cao

    Published 2025-01-01
    “…Experiments demonstrate that the optimization capacity of the IDBO algorithm is conspicuously superior to other intelligent optimization algorithms, and the IDBO-GRU algorithm surpasses the probabilistic neural network (PNN) and the GRU algorithm in the denoising accuracy of WFEM data. …”
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    Article
  14. 2014

    A Defect Detection Algorithm for Optoelectronic Detectors Utilizing GLV-YOLO by Xinfang Zhao, Qinghua Lyu, Hui Zeng, Zhuoyi Ling, Zhongsheng Zhai, Hui Lyu, Saffa Riffat, Benyuan Chen, Wanting Wang

    Published 2025-02-01
    “…To meet the demands of real-time and accurate defect detection, this paper introduces an optimization algorithm based on the GLV-YOLO model tailored for photodetector defect detection in manufacturing settings. …”
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    Article
  15. 2015
  16. 2016
  17. 2017

    Vibration Analysis and Optimization of Iron-Core Reactors Based on Fe-Based Soft Magnetic Composite Materials by Yangyang Ma, Wenle Song, Jie Gao, Yang Liu, Yilei Shang, Weimei Zhao, Fuyao Yang

    Published 2025-01-01
    “…The characteristic parameters of the improved model are identified using the particle swarm optimization–simulated annealing (PSO-SA) algorithm, with the identified root mean square error not exceeding 3.5, verifying the model’s accuracy. …”
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    Article
  18. 2018

    METAHEURISTIC-AI ENHANCED CUSTOM DEEP LEARNING NETWORK OPTIMIZED WITH SAND CAT SWARM ALGORITHM FOR ORAL CANCER DIAGNOSIS by Vinod Kumar Venkatesan, V Sujatha, Audithan Sivaraman, S Durga Devi, Praveen SR Konduri

    Published 2025-06-01
    “…The CNN architecture is designed to automatically extract discriminative features from images, while the SCSO algorithm fine-tunes crucial hyperparameters such as learning rate, batch size, and dropout rate to enhance model performance. …”
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    Article
  19. 2019

    Multi-objective optimization framework for electric vehicle charging and discharging scheduling in distribution networks using the red deer algorithm by Sahbi Boubaker, Habib Kraiem, Nejib Ghazouani, Souad Kamel, Adel Mellit, Faisal S. Alsubaei, Farid Bourennani, Walid Meskine, Tariq Alqubaysi

    Published 2025-04-01
    “…To tackle the optimization problem, a metaheuristic swarm intelligence algorithm, the Red Deer Algorithm (RDA), is utilized to determine the optimal EV charging and discharging timings. …”
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    Article
  20. 2020

    Improving stroke risk prediction by integrating XGBoost, optimized principal component analysis, and explainable artificial intelligence by Lesia Mochurad, Viktoriia Babii, Yuliia Boliubash, Yulianna Mochurad

    Published 2025-02-01
    “…Abstract The relevance of the study is due to the growing number of diseases of the cerebrovascular system, in particular stroke, which is one of the leading causes of disability and mortality in the world. To improve stroke risk prediction models in terms of efficiency and interpretability, we propose to integrate modern machine learning algorithms and data dimensionality reduction methods, in particular XGBoost and optimized principal component analysis (PCA), which provide data structuring and increase processing speed, especially for large datasets. …”
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