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  1. 6361

    A Robust Enhanced Ensemble Learning Method for Breast Cancer Data Diagnosis on Imbalanced Data by Zhenzhen Wang, Junde Xie, Jia Zhang

    Published 2024-01-01
    “…In addition, a data-driven based particle swarm optimization algorithm automatically is used to select the value of parameters for base classifiers. …”
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    Article
  2. 6362

    Performance Analysis of CO2 Systems Integrated with Ejector and Dedicated Mechanical Subcooling by Dai Baomin, Zhao Ruirui, Liu Shengchun, Qian Jiabao, Xu Tianyahui, Liu Chen, Yang Peifang

    Published 2023-01-01
    “…A thermodynamic model of the system was devised. Then, the discharge pressure and subcooling degree were optimized using a genetic algorithm by considering the coefficient of performance (COP) as the objective function. …”
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    Article
  3. 6363

    Maximum Energy Absorbed from the Persian Gulf Waves Considering Uncertainty in Power Take off Parameters by Mohammad Jalali, Reihaneh Kardehi Moghaddam, Naser Pariz

    Published 2022-06-01
    “…Compared to particle swarm optimization and conventional black hole algorithm, the results of the proposed method indicate enhancements in reference velocity tracking and absorbed power. …”
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    Article
  4. 6364

    Cluster channel equalization using adaptive sensing and reinforcement learning for UAV communication by Xin Liu, Shanghong Zhao, Yanxia Liang, Shahid Karim

    Published 2024-12-01
    “…Finally, we construct the U-FRQL-EA equalization algorithm by combining the improved U-Net model with fuzzy reinforcement Q-learning. …”
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    Article
  5. 6365

    High-throughput end-to-end aphid honeydew excretion behavior recognition method based on rapid adaptive motion-feature fusion by Zhongqiang Song, Jiahao Shen, Qiaoyi Liu, Wanyue Zhang, Ziqian Ren, Kaiwen Yang, Xinle Li, Jialei Liu, Fengming Yan, Wenqiang Li, Yuqing Xing, Lili Wu

    Published 2025-07-01
    “…Compared with the model excluding the RK50 module, the mAP50 improved by 2.9%, and its performance in detecting small-target honeydew significantly surpassed mainstream algorithms. …”
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    Article
  6. 6366

    Research on action matching of skeletal point coordinates and sports teaching application based on Open-pose by Shunmin Su

    Published 2025-12-01
    “…This study addresses the challenges of high matching errors and low recognition rates in traditional skeletal point-based human action matching methods, a skeleton point coordinate and human posture action matching technology is studied based on Open-pose open-source model. Based on the Open-pose open source model, we construct a skeletal point coordinate action matching network model, use the feed-forward network for 2D confidence mapping, test it through the loss function, calculate the shortest distance to identify the association affinity domain, and introduce the greedy relaxation algorithm to optimize the accuracy rate of the association matching of multi-body skeletal points; we obtain the skeletal point coordinate parameters through the two-dimensional spatial mapping and use the k-means algorithm to quantify the features of the skeletal point coordinates, and the residuals of the skeletal point coordinates are quantized. …”
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  7. 6367

    Federated learning for digital twin applications: a privacy-preserving and low-latency approach by Jie Li, Dong Wang

    Published 2025-08-01
    “…Our approach introduces an improved Paillier encryption method with a new hyperparameter and pre-calculates multiple random intermediate values during the key generation stage, significantly reducing encryption time and thereby expediting model training. …”
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    Article
  8. 6368

    Research on pedestrian detection technology for mining unmanned vehicles by ZHOU Libing, YU Zhengqian, WEI Jianjian, JIANG Xueli, YE Baisong, ZHAO Yexin, YANG Siliang

    Published 2024-10-01
    “…To tackle issues of missed detections and low accuracy in pedestrian detection, an improved YOLOv3-based pedestrian detection algorithm for mining unmanned vehicles was introduced. …”
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    Article
  9. 6369

    Network-coding-based two-way relay cooperation with energy harvesting by Shunwai Zhang, Rongfang Song, Tao Hong

    Published 2017-04-01
    “…Furthermore, we analyze the outage probability and bit error rate of the system when the optimal antenna selection algorithm is adopted at the relay to transmit data. …”
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    Article
  10. 6370

    Electric vehicle charging load prediction method based on multi-objective modal decomposition and NAHL neural network by GUO Xinzhe, WANG Yeqin, WANG Chao, WU Mingjiang, YANG Yan, ZHANG Chu

    Published 2025-03-01
    “…The improved NSGAII-LDSBX algorithm is used to optimize the parameters of VMD, decompose the signal into several subsequences, and reconstruct the subsequences through fuzzy entropy (FE). …”
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    Article
  11. 6371

    Soft Measurement of Wastewater Treatment System Based on PSOGA-WNN by LIU Yuhui, MAI Wenjie, LI Xiaoyong, ZHAO Yinzhong, HE Xinzhong, HUANG Mingzhi

    Published 2023-01-01
    “…To accurately predict the SS<sub>eff</sub> (effluent SS) content and COD<sub>eff</sub> (effluent COD) concentration in water quality parameters and further improve the water quality early warning mechanism,this paper proposes the PSOGA-WNN soft measurement model of paper wastewater effluent quality to obtain the main water quality technical parameters,COD<sub>inf</sub> (influent COD),Q (influent flow),pH (influent pH),SS<sub>inf</sub> (influent SS),T (influent temperature),DO (influent dissolved oxygen),COD<sub>eff</sub>,and SS<sub>eff,</sub> for predicting the quality of wastewater from the wastewater treatment plant.Among them,the prediction results of PSOGA-WNN are compared with the neural networks of PSO-WNN,GA-WNN,and PSOGA-BP.The results show that the PSOGA-WNN neural network has the highest prediction accuracy,which indicates that the PSOGA hybrid parameter optimization algorithm based on the genetic algorithm and particle swarm algorithm has obvious superiority in optimizing the prediction accuracy of the model.The WNN neural network has certain advantages over BP neural network in terms of fitting degree as well as error accuracy and is an effective means of simulation prediction.…”
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  12. 6372

    Resource Scheduling with Uncertain Execution Time in Cloud Computing by LI Cheng-yan, CAO Ke-han, FENG Shi-xiang, SUN Wei

    Published 2019-02-01
    “…For the problem of cloud computing resource scheduling, based on the fuzzy programming theory, a fuzzy cloud resource scheduling model under timecost constraint was set up, the uncertain execution time of tasks is represented by the triangular fuzzy number, and the target is to minimize the average value and standard deviation of the evaluation function An improved chaotic ant colony algorithm was proposed to solve the model, the elitist strategy is introduced to optimize the pheromone updating, a chaotic mapping with infinite folding times is used for chaotic search, and the adaptive chaotic disturbance mechanism is designed to enhance the global searching ability The model and algorithm were tested on the Cloudsim platform, the reliability of the model was proved, and the experimental results showed that the proposed algorithm had better performance in convergence speed, solution ability and load balance…”
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  13. 6373
  14. 6374

    Influence of artificial intelligence on higher education reform and talent cultivation in the digital intelligence era by Limin Qian, Weiran Cao, Lifeng Chen

    Published 2025-02-01
    “…Abstract In order to solve the problems of inefficient allocation of teaching resources and inaccurate recommendation of learning paths in higher education, this paper proposes a smart education optimization model (SEOM) by combining the improved random forest algorithm (RFA) based on adaptive enhancement mechanism and the Graph Neural Network (GNN) algorithm. …”
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  15. 6375

    High-Precision Pose Measurement of Containers on the Transfer Platform of the Dual-Trolley Quayside Container Crane Based on Machine Vision by Jiaqi Wang, Mengjie He, Yujie Zhang, Zhiwei Zhang, Octavian Postolache, Chao Mi

    Published 2025-04-01
    “…An enhanced EPnP optimization algorithm incorporating lockhole coplanar constraints is proposed, establishing a 2D–3D coordinate transformation model that reduces pose-estimation errors to millimeter level (planar MAE-P = 0.024 m) and sub-angular level (MAE-<inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mi>θ</mi></semantics></math></inline-formula> = 0.11°). …”
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  16. 6376

    Energy Harvesting for Throughput Enhancement of Cooperative Wireless Sensor Networks by Van-Dinh Nguyen, Chuyen T. Nguyen, Oh-Soon Shin

    Published 2016-07-01
    “…We then propose an iterative power allocation algorithm which converges to a locally optimal solution at a Karush-Kuhn-Tucker point. …”
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    Article
  17. 6377

    Automatic Identification and Segmentation of Overlapping Fog Droplets Using XGBoost and Image Segmentation by Dongde Liao, Xiongfei Chen, Muhua Liu, Yihan Zhou, Peng Fang, Jinlong Lin, Zhaopeng Liu, Xiao Wang

    Published 2025-03-01
    “…In order to accurately measure the droplet size and grasp the droplet distribution pattern, this study proposes a method based on the optimized XGBoost classification model combined with improved concave-point matching to achieve multi-level overlapping-droplet segmentation. …”
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    Article
  18. 6378

    Automatic license-plate recognition by A. V. Poltavskii, T. G. Yurushkina, M. V. Yurushkin

    Published 2020-03-01
    “…Quality of the system is provided through the optimization of various models with different modifications. …”
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    Article
  19. 6379

    PolicySegNet: a policy-based reinforcement learning framework with pretrained embeddings and transformer decoder for joint brain tumors segmentation and classification in MRI by Vishv Patel, Vandana Patel, Aakash Shinde

    Published 2025-08-01
    “…PolicySegNet uniquely integrates a policy-based reinforcement learning algorithm—specifically proximal policy optimization (PPO)—to jointly optimize the decoder and classifier based on a reward signal that balances segmentation accuracy with classification performance. …”
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    Article
  20. 6380

    Detection of false data injection in electric energy metering platforms using gradient lifting decision trees and MLP neural networks by Yakui Zhu, Yangrui Zhang, Chao Zhang, Bingyu Zhang, Hongying Wang, Shaokang Feng

    Published 2024-12-01
    “…The discriminator used a multilayer perceptron (MLP) neural network, combined with difference analysis between the predicted and actual values, to determine false data injection. The improved Cauchy mutation grey Wolf optimization algorithm is used to optimize the model training to improve the detection accuracy. …”
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    Article