Combined Allocation of Renewable-Based Distributed Generators and Shunt Capacitor Banks in Distribution Networks with Electric Vehicle Load Penetration by Abhilasha Pawar, Rajkumar Viral, Divya Asija, Mohit Bansal

“…Compared to other optimization algorithms, the APO shows superior performance. …”
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The Influence Mechanism of Narrative Strategies Used by Virtual Influencers on Consumer Product Preferences by Yuelong Zeng, Gefei Pu, Jingwen Liu, Wenting Feng

“…As social media has risen, virtual social media influencers have become a significant tool in modern marketing, utilizing computer-generated images (CGI), machine learning algorithms, and artificial intelligence technologies to connect with consumers via virtual online personas. …”
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Data-Driven Revolution in Academic Support for Mathematics Underachievers through Random Forest Individual and Hybrid Model by Asadi Srinivasulu, Vanithamani Palanisamy

“…Educational Data Mining, leveraging machine learning and data mining techniques, aims to predict student performance using available datasets. …”
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DEVELOPMENT METHODS FOR CALCULATING POWER LOSSES AND THE VOLTAGE LEVELS IN COMPLEX DISTRIBUTION NETWORKS by I. M. Valeev, Ha. D. Nguyen

“…The paper presents an analysis and evaluation of the effectiveness different methods for reduction the power loss and voltage in the distribution networks by changing and building a new network topology using the software PSS/ADEAPT. …”
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Cylinder Position Servo Control Based on Fuzzy PID by Shibo Cai, Shunlei Wu, Guanjun Bao

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Objectively measured environmental factors in relation to school travel mode among adolescents: a decision tree analysis by Lena Malnes, Tommy Haugen, Emma Charlott Andersson Nordbø, Andreas Ivarsson, Elin Kolle, Geir Kåre Resaland, Runar Barstad Solberg, Andreas Åvitsland, Sveinung Berntsen

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Energy-Efficient Distributed Compressed Sensing Data Aggregation for Cluster-Based Underwater Acoustic Sensor Networks by Deqing Wang, Ru Xu, Xiaoyi Hu, Wei Su

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Fusion Classification Method Based on Audiovisual Information Processing by Peiju Chen, Xuan Zhang, Huijun Zhao, Huiliang Cao, Xuemei Chen, Xiaochen Liu

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Design and optimization of planetary gear train pendulum type sugarcane seeding mechanism based on spatial offset trajectory by Jiaodi Liu, Chaoyuan Luo, Qingli Chen, Jianhao Chen, Jianlong Chen, Yihao Xing

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Two-layer multi-objective optimal sizing of electric-hydrogen energy storage with the integration of extreme scenario generation and preference-information decision-making by Zihan Sun, Jian Chen, Yang Chen, Wen Zhang, Tingting Zhang, Yicheng Zhang, Guangsheng Pan

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Modeling of biodiesel production using optimization designs from literature: aiming to reduce the laboratory workload by Iver Bergh Hvidsten, Kristian Hovde Liland, Oliver Tomic, Jorge Mario Marchetti

“…The global GBR model was comprehensively evaluated for accuracy and physical relevance, with proposed applications in component screening and reaction optimization using the DIRECT-l (DIviding RECTangles - locally biased version) algorithm. Additionally, an experimental reaction was optimized via the global model and DIRECT-l, then refined using a retrained local model for improved system-specific predictions. …”
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Phase Space Similarity as a Signature for Rolling Bearing Fault Diagnosis and Remaining Useful Life Estimation by Fang Liu, Bing He, Yongbin Liu, Siliang Lu, Yilei Zhao, Jiwen Zhao

“…Based on the PSS, a fault pattern recognition algorithm, a bearing fault size prediction algorithm, and a RUL estimation algorithm are introduced to analyze the experimental signal. …”
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基于多重分形谱的转子系统故障诊断与参数优选 by 刘岩, 王金东, 郭建华, 胡清明

“…Because of the robustness of one dimensional time series reconstruction G-P algorithm to extract the fault omen is poor,especially influenced by a sensitive noise in the measured signal.A noise reduction method is proposed based on detrended fluctuat ion analysis（FDA） and kernel principal component analysis（KPCA）,the eigenvalue extraction algorithm based on Mult ifractal spectrum is presented.Through pseudo-phase portrait to determine the weighting factor threshold,optimize and choose parameter and compare with the defects of single G_P algorithm,and combine with the 3 kinds of rotor system common faults,the stability and accuracy of eigenvalue extraction of this method is analyzed,the results prove that,the diagnosis result is good.…”
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基于正态反高斯模型的自适应小波消噪方法 by 吴国洋

“…A locally adaptive wavelet de-noising method based on normal inverse Gaussian modal is proposed.Firstly,the db5 wavelet is used to decompose the signal.For those wavelet coefficients which contain a lot of noise,the normal inverse Gaussian modal with good approximation property is constructed as the prior distribution model of those coefficients,on the basis of the model,Bayesian maximum a posteriori estimator is used to estimate the noisy wavelet coefficients and got the realistic wavelet coefficients.Then in the process of posteriori estimation,in order to get the best posteriori approximation model,the particle swarm optimization algorithm is used to select the key coefficient of the model.Finally,new wavelet coefficients are used for the reconstruction of the de-noised signal,and the de-noised signal is gotten.The algorithm is analyzed by simulation and bearing fault signal respectively.Analysis results show that this algorithm has good noise reduction effect,and can efficiently reduce the noise.…”
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A multi-task genetic programming approach for online multi-objective container placement in heterogeneous cluster by Ruochen Liu, Haoyuan Lv, Ping Yang, Rongfang Wang

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Pyo-septic complications of severe necrotizing forms of acute pancreatitis by N. N. Veligotsky, S. E. Arutyunov, M. V. Klymenko, K. A. Aleksanyan

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Efficient Markerless Motion Classification Using Radar by Changhyeon Eom, Sooji Han, Sabin Chun, Soyoung Joo, Jisu Yoon, Min Kim, Jongchul Park, Sanghong Park

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Deep-Learning-Based Approach in Imaging Radiometry by Aperture Synthesis: Application to Real SMOS Data by Ali Khazaal, Richard Faucheron, Nemesio J. Rodriguez-Fernandez, Eric Anterrieu

“…A novel image reconstruction algorithm for aperture synthesis measurements using deep learning techniques was introduced recently. …”
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Multi-omics analysis and experiments uncover the link between cancer intrinsic drivers, stemness, and immunotherapy in ovarian cancer with validation in a pan-cancer census by Yilin Li, Cen Chen, Xiaoyu Ji, Ningxiao Jiang, Fei Wang, Xiangqian Gao, Weiwei Chen, Qiang Tang, Yan Li, Shinan Zhang, Gaofeng Qin, Yingjiang Xu, Yanlin Wang, Lingwen Kong, Lei Han, Jie Mei

“…We then developed the CSCI to predict the prognosis and response to immunotherapy in ovarian cancer patients using advanced machine learning algorithms. …”
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Ensemble machine learning model for forecasting wind farm generation by A. G. Rusina, Osgonbaatar Tuvshin, P. V. Matrenin, N. N. Sergeev

“…This study is carried out by ensemble algorithms, such as Random Forest, AdaBoost and XGBoost, which are one of the machine learning approaches. …”
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