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  1. 5881

    Outdoor location scheme with fingerprinting based on machine learning of mobile cellular network by Zhichao ZHOU, Yi FENG, Xiaohan XIA, Yuyao FENG, Chao CAI, Jiahui QIU, Lihui YANG, Yunxiao WU

    Published 2021-08-01
    “…The positioning scheme based on mobile cellular network technology is one of the important technical approaches to provide network optimization, emergency rescue, police patrol and location services.The traditional positioning scheme based on cell base station location information has low positioning accuracy and large positioning error, so it cannot meet the requirements of some positioning applications.The scheme based on fingerprint location can greatly improve the location accuracy, save computational cost and enhance the usability based on the coarse location scheme of the cell and become the hotspot of the research.Rasterization and non-rasterization of outdoor fingerprint location scheme based on machine learning were studied and analyzed to meet the business requirements of outdoor fingerprint location.By means of parameter weighting, data fitting and other methods, large-scale fingerprint data were cleaned to improve the effectiveness of data sources.Through the realization of sub-modules such as demarcating research area, rasterizing, constructing fingerprint database, training model, correcting model, non-rasterizing, rough positioning coupling, matching parameter and training parameter, the operation efficiency and positioning accuracy of the algorithm were analyzed and optimized, and the key indexes affecting the algorithm performance were determined.Then, the performance of two fingerprint-based localization schemewas analyzed based on the simulation results.Finally, the typical scenarios of the fingerprint location scheme based on machine learning in practical application were presented.…”
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  2. 5882

    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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  3. 5883

    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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  4. 5884

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

    Published 2022-01-01
    “…Then, the BP neural network is improved by using particle swarm optimization (PSO) combined with the simulated annealing algorithm. …”
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  5. 5885

    Breast Tumor-Like-Masses Segmentation From Scattering Images Obtained With an Ultrahigh-Sensitivity Talbot-Lau Interferometer Using Convolutional Neural Networks by Ionut-Cristian Ciobanu, Nicoleta Safca, Elena Anghel, Dan Popescu

    Published 2025-01-01
    “…U-Net demonstrated the most stable performance with an accuracy of 86.34% and an F1-score of 90.2%, making it the most reliable model for tumor segmentation in scattering images. …”
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  6. 5886

    Flight Endurance Increasing Technology of New Energy UAV Based on a Strut-Braced Wing by Li Liu, Wencan Bai, Dun Yang

    Published 2022-01-01
    “…Surrogate model technology and multiobjective genetic algorithm are used to optimize the SBW configuration. …”
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  7. 5887

    Dynamic-budget superpixel active learning for semantic segmentation by Yuemin Wang, Ian Stavness

    Published 2025-01-01
    “…A static budget could result in over- or under-labeling images as the number of high-impact regions in each image can vary.MethodsIn this paper, we present a novel dynamic-budget superpixel querying strategy that can query the optimal numbers of high-uncertainty superpixels in an image to improve the querying efficiency of regional active learning algorithms designed for semantic segmentation.ResultsFor two distinct datasets, we show that by allowing a dynamic budget for each image, the active learning algorithm is more effective compared to static-budget querying at the same low total labeling budget. …”
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  8. 5888

    Investigation on the Aerodynamic Parameters of the Triangle Shape of Tall Buildings by Using of CFD Method by Mehdi Noormohamadian, Eysa Salajegheh

    Published 2023-01-01
    “…Nowadays, the neural network algorithm is one of the most famous numerical methods for optimizing hull shapes. …”
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  9. 5889

    Research on management mode of talent team in E-government based on big data analysis by Shixuan Hao

    Published 2025-12-01
    “…The performance analysis of the Apriori algorithm before and after improvement shows that the optimized Apriori algorithm can significantly reduce the number of scans of the data transaction database and the system running time, and the algorithm efficiency has increased by 48.26 %. …”
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  10. 5890

    Research on deep reinforcement learning in Internet of vehicles edge computing based on Quasi-Newton method by ZHANG Jianwu, LU Zetao, ZHANG Qianhua, ZHAN Ming

    Published 2024-05-01
    “…Additionally, system transmission time allocation in the vehicular network model was considered, enhancing the practicality of the algorithm. …”
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  11. 5891

    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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  12. 5892

    Based on PCA and SSA-LightGBM oil-immersed transformer fault diagnosis method. by Jizhong Wang, Jianfei Chi, Yeqiang Ding, Haiyan Yao, Qiang Guo

    Published 2025-01-01
    “…The experimental results show that the SSA-LightGBM model proposed in this paper has an average fault diagnosis accuracy of 93.6% after SSA algorithm optimization, which is 3.6% higher than before optimization. …”
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  13. 5893

    基于分层模糊优化的湿式多片离合器起步控制研究 by 闫光辉, 关志伟, 童敏勇

    Published 2012-01-01
    “…According to the control theory of wet multi-plate clutch and starting process,taking full account of starting impact and sliding friction works,the starting process is analyzed and the control parameters of each starting process are selected.And then the hierarchical fuzzy optimization control strategy of clutch engagement occupation-empty ratio is proposed,which means the first analysis of starting intention,followed by initial occupation-empty ratio control,and finally to optimize occupation-empty ratio.Based on the control strategy,the control model and algorithm of hierarchical fuzzy optimization is designed.After vehicle simulation and compare with other control strategies,the results show that the strategy can effectively identify the driver’s starting intention,improve the smoothness of the wet clutch and reduce the starting impact and sliding friction works.…”
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  14. 5894

    Torsional Stiffness Correction of the Split-Type Triple-Box Steel Box Girder Based on Refined Simulation by Yu Tang, Min Xu, Jie Yue, Shixiong Zheng

    Published 2021-01-01
    “…Then, the beam element is used for conventional modelling of the bridge, and artificial bee colony (ABC) algorithm is adopted for the optimization and correction of structure parameters of the BEM of the girder. …”
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  15. 5895

    Underwater acoustic channel estimation method based on response generative network by XU Ming, ZHANG Qi

    Published 2025-04-01
    “…The input signal of the generative network was updated by a weight and bias update algorithm based on L1-regularized least squares. Finally, to address the instability of traditional deep learning models for underwater acoustic signals, a decomposed optimization algorithm based on Bures-Wasserstein objective function was proposed. …”
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  16. 5896

    HUMAN-ORIENTED QUALITY MANAGEMENT SYSTEM OF ENTERPRISE: CONTROL OF NON-CONFORMING PRODUCT AND UTILIZATION by Vyacheslav Feoktistovich Bezyazychny, Maria Evgenyevna Ilyina

    Published 2013-09-01
    “…The presented model algorithm reflects all possible action variants directed on the improvement and the most effective use of non-conforming product. …”
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  17. 5897

    A multitask framework based on CA-EfficientNetV2 for the prediction of glioma molecular biomarkers by Qian Xu, Feng Ning Liang, Ya Ru Cao, Jin Duan, Teng Cui, Teng Zhao, Hong Zhu

    Published 2025-07-01
    “…Initially, unlabeled MR images were annotated using K-means clustering to generate pseudolabels, which were subsequently refined using a Vision Transformer (ViT) network to improve labeling accuracy. Then, the Fruit Fly Optimization Algorithm (FOA) was employed to assign optimal weights to the pseudolabeled data. …”
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  18. 5898

    Energy Storage Regulation Method of Base Stations in 5G Integrated Distribution Network Based on Energy Sharing and Trading Coordination by Yanru WANG, Xiyang YIN, Qinghai OU, Wenjie MA, Hui LIU, Zhigang DU

    Published 2023-06-01
    “…Then, with the optimization objectives of promoting energy sharing of 5G base stations, improving operation efficiency of base stations, and participating in peak shaving and valley filling, the optimization problem of energy storage regulation of base stations in a 5G integrated distribution network is constructed, and an energy storage regulation algorithm of 5G base stations based on energy sharing and trading coordination is proposed. …”
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  19. 5899

    Multi-Objective Technology-Based Approach to Home Healthcare Routing Problem Considering Sustainability Aspects by Ahmed Adnan Zaid, Ahmed R. Asaad, Mohammed Othman, Ahmad Haj Mohammad

    Published 2024-07-01
    “…<i>Methods</i>: The model was solved using a metaheuristic algorithm approach via the Ant Colony Optimization algorithm and the Non-Dominated Sorting technique due to the ability of such a combination to work out with dynamic models with uncertainties and multi-objectives. …”
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  20. 5900

    Performance Evaluation of Intrusion Detection System using Selected Features and Machine Learning Classifiers by Raja Azlina Raja Mahmood, AmirHossien Abdi, Masnida Hussin

    Published 2021-06-01
    “…Moreover, using the most relevant features to build the predictive model, reduces the complexity of the developed model, thus reducing the building classifier model time and consequently improves the detection performance.  …”
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