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Showing 121 - 140 results of 3,247 for search 'improved (whale OR while) optimization algorithm', query time: 0.20s Refine Results
  1. 121

    Optimizing Cancer Detection: Swarm Algorithms Combined with Deep Learning in Colon and Lung Cancer using Biomedical Images by HariKrishna Pathipati, Lova Naga Babu Ramisetti, Desidi Narsimha Reddy, Swetha Pesaru, Mashetty Balakrishna, Thota Anitha

    Published 2025-03-01
    “…Also, the hybrid of convolutional bidirectional gated recurrent unit (CNN‐BiGRU) model was applied for classifying the existence of colon and lung cancer in the biomedical images. Eventually, the whale optimization algorithm (WOA) is used to optimally choose the hyperparameters of the CNN‐BiGRU model. …”
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    Article
  2. 122

    Route Optimization for UVC Disinfection Robot Using Bio-Inspired Metaheuristic Techniques by Mario Peñacoba, Eduardo Bayona, Jesús Enrique Sierra-García, Matilde Santos

    Published 2024-12-01
    “…Bio-inspired metaheuristic algorithms such as the gazelle optimization algorithm, whale optimization algorithm, bat optimization algorithm, and particle swarm optimization are applied. …”
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    Article
  3. 123

    Improved Coyote Optimization Algorithm for Optimally Installing Solar Photovoltaic Distribution Generation Units in Radial Distribution Power Systems by Thang Trung Nguyen, Thai Dinh Pham, Le Chi Kien, Le Van Dai

    Published 2020-01-01
    “…This paper proposes an improved coyote optimization algorithm (ICOA) for optimizing the location and sizing of solar photovoltaic distribution generation units (PVDGUs) in radial distribution systems. …”
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    Article
  4. 124

    Hybrid Improved PSO Algorithm for Soil Property Parameter Estimation by Mude Li, Aiping Shi, Yefan Shi, Tao Zhang, Cu Qu, Lihua Ye

    Published 2025-04-01
    “…For multimodal functions (e.g., F3), PSO-EDO significantly outperforms PSO-WOA (Particle Swarm Optimization-Whale Optimization Algorithm) with a 22.3% reduction in error. …”
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    Article
  5. 125

    Study on Multiobjective Path Optimization of Plant Protection Robots Based on Improved ACO‐DWA Algorithm by Jing Niu, Chuanyan Shen, Lipeng Zhang, Guanghao Gao, Jiahao Zheng

    Published 2025-02-01
    “…To address the false judgment of visual information caused by the shading of branches and leaves and the difficulty in avoiding obstacles in complex orchard terrain, an operation trajectory optimization approach based on the improved dynamic window algorithm (DWA) with ant colony optimization (ACO) was developed. …”
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    Article
  6. 126

    Research on Springback Compensation Method of Roll Forming Based on Improved Fuzzy PID Control by Tengqiang Wang, Yingping Qian, Wengkang Fang, Dongqiao Zhang, Huanqi Weng, Yiran Jiang

    Published 2025-03-01
    “…To realize the precise control required by the springback compensation control strategy, a fuzzy PID controller strategy optimized by the coupled whale particle (CWP) algorithm is designed. …”
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    Article
  7. 127

    Integration of electric vehicle charging stations with distributed generation using multi-objective metaheuristic optimization by Aya Desoky Gaber, E.M. Abdallah, M.I. Elsayed, Ahmed Abdelbaset

    Published 2025-09-01
    “…This paper uses a multi-objective optimization approach metaheuristic algorithm, specifically the Whale Optimization Algorithm (WOA), Zebra Optimization Algorithm (ZOA), and Puma Optimization Algorithm (POA), to determine the optimal size and placement of DG units in the presence of EVCS. …”
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    Article
  8. 128

    Improvement teaching-learning-based optimization algorithm for solar cell parameter extraction in photovoltaic systems by H. Khaterchi, M. H. Moulahi, A. Jeridi, R. Ben Messaoud, A. Zaafouri

    Published 2025-05-01
    “…Goal. The work aims to improve the Teaching-Learning-Based Optimization (TLBO) algorithm to enhance the accuracy of parameter extraction in PV models. …”
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    Article
  9. 129

    Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

    Published 2021-03-01
    “…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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    Article
  10. 130

    Prediction method of soil water content based on SVM optimized by improved salp swarm algorithm by Xiaoqiang ZHAO, Fan YANG, Zhufeng YAN

    Published 2021-03-01
    “…Aiming at the problems of low accuracy and low efficiency of traditional soil water content prediction methods, support vector machine (SVM) was used to establish a prediction model, and the soil water content prediction method based on SVM optimized was proposed by the improved salp swarm algorithm.Firstly, the opposition-based learning and chaotic optimization were introduced to improve the standard salp swarm algorithm to solve the problem that the algorithm was easy to fall into the local optimal solution and its convergence speed was slow.Secondly, the improved salp swarm algorithm was used to optimize the parameters that affect the performance of SVM and the corresponding prediction model was built.Finally, the proposed model was compared with the particle swarm optimization SVM and the whale algorithm optimized SVM prediction model.The experimental results show that the mean square error and decision coefficient of the proposed model are 0.42 and 0.901, which are better than the other two models which verified the effectiveness of the proposed method.…”
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    Article
  11. 131

    Multi-objective optimization analysis of construction management site layout based on improved genetic algorithm by Hui Yin

    Published 2024-12-01
    “…The results show that in terms of computational time, the genetic algorithm takes an average of 1702.0 s, while the improved algorithm takes an average of 421.0 s, which is 1281s less and 85.9% more than before the improvement. …”
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    Article
  12. 132

    Application of Optimal Scheduling Model Based on Improved Genetic Algorithm in Electric Power Mobile Operation by Rui Fan, Huiying Jing, Zhixin Jing

    Published 2024-01-01
    “…In order to solve the current situation, an optimized scheduling model for power mobile jobs based on improved genetic algorithm is proposed. …”
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    Article
  13. 133

    An Improved Human Evolution Optimization Algorithm for Unmanned Aerial Vehicle 3D Trajectory Planning by Xue Wang, Shiyuan Zhou, Zijia Wang, Xiaoyun Xia, Yaolong Duan

    Published 2025-01-01
    “…To address the challenges of slow convergence speed, poor convergence precision, and getting stuck in local optima for unmanned aerial vehicle (UAV) three-dimensional path planning, this paper proposes a path planning method based on an Improved Human Evolution Optimization Algorithm (IHEOA). …”
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    Article
  14. 134

    Low-Power Intelligent Wireless Sensor Network for Precision Agriculture Oriented Agricultural Greenhouse Management System by Hongguo Jin

    Published 2025-01-01
    “…When the number of sensor nodes was 100, the improved whale optimization algorithm accounted for only 15% of the routing energy consumption, while the simulated annealing algorithm accounted for 53% of the routing energy consumption. …”
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    Article
  15. 135

    An Improved Multi-Objective Adaptive Human Learning Optimization Algorithm and Its Application in Optimizing Formulation Schemes for Rotary Hearth Furnaces by Jun Yao, Songcheng Zhou, Ling Wang, Xianxia Zhang

    Published 2025-06-01
    “…An improved multi-objective adaptive human learning optimization algorithm (IMOAHLO) is proposed, which enhances local optimization through neighborhood search and an adaptive learning mechanism. …”
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    Article
  16. 136

    An improved dung beetle optimizer based on Padé approximation strategy for global optimization and feature selection by Tianbao Liu, Lingling Yang, Yue Li, Xiwen Qin

    Published 2025-03-01
    “…This strategy effectively improved the algorithm's ability to jump out of the local optimal and explore potential candidate solutions. …”
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    Article
  17. 137

    Hybrid Attention-Enhanced Xception and Dynamic Chaotic Whale Optimization for Brain Tumor Diagnosis by Aliyu Tetengi Ibrahim, Ibrahim Hayatu Hassan, Mohammed Abdullahi, Armand Florentin Donfack Kana, Amina Hassan Abubakar, Mohammed Tukur Mohammed, Lubna A. Gabralla, Mohamad Khoiru Rusydi, Haruna Chiroma

    Published 2025-07-01
    “…The methodology is built on a combination of preprocessing techniques, transfer learning architecture reconstruction, and dynamic fine-tuning strategies. To optimize key hyper-parameters, this study employed the Dynamic Chaotic Whale Optimization Algorithm. …”
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    Article
  18. 138

    Control Strategy of a Rotating Power Flow Controller Based on an Improved Hybrid Particle Swarm Optimization Algorithm by Ziyang Zhang, Jiaoxin Jia, Waseem Aslam, Abubakar Siddique, Fahad R. Albogamy

    Published 2025-02-01
    “…Notably, this paper introduces intelligent optimization algorithms to this field for the first time, employing an improved hybrid particle swarm optimization (HPSO) algorithm to control the active power while keeping the reactive power constant and subsequently adjusting the reactive power while maintaining the active power steady, thereby achieving power regulation. …”
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    Article
  19. 139
  20. 140

    Application of bioinspired global optimization algorithms to the improvement of the prediction accuracy of compact extreme learning machines by L. A. Demidova, A. V. Gorchakov

    Published 2022-04-01
    “…By adjusting input weights with bioinspired optimization algorithms, it was shown that the prediction accuracy of ELMs in regression problems can be improved to reduce the number of hidden-layer neurons to reach a high prediction accuracy on learning and test datasets. …”
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    Article