Distribution Ratio Prediction of Major Components in 30%TBP/kerosene-HNO3 System Based on Machine Learning by YU Ting1, ZHANG Yinyin2, ZHANG Ruizhi3, JIN Wenlei2, LUO Yingting2, ZHU Shengfeng3, HE Hui1, YE Guoan1, GONG Helin4

“…These models were trained based on different datasets, and their hyper-parameters were optimized using algorithms such as grid search, Bayesian optimization, and K-fold cross-validation. …”

Operation Optimization of Multiphase Pollutant Treatment Considering Carbon Emissions by Guo Yu, Dongjie Zhang, Hailong Deng, Chao Jiang, Quanling Zhang

“…Aiming to improve the treatment of multiphase pollutants, this study builds a three-objective optimization model by considering the optimization of treatment effect, energy consumption, and an innovatively constructed optimization objective of direct and indirect carbon emissions. …”
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Priority-Aware Spectrum Management for QoS Optimization in Vehicular IoT by Adeel Iqbal, Tahir Khurshaid, Yazdan Ahmad Qadri, Ali Nauman, Sung Won Kim

“…A Continuous-Time Markov Chain (CTMC) model is derived to analyze the proposed algorithm for various network loads. …”
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Offline Magnetometer Calibration Using Enhanced Particle Swarm Optimization by Lei Huang, Zhihui Chen, Jun Guan, Jian Huang, Wenjun Yi

“…First, a magnetometer calibration model is established. Second, the DAEPSO algorithm is employed to fit the ellipsoid parameters. …”
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Optimization of an Intelligent Music-Playing System Based on Network Communication by Liaoyan Zhang

“…The recommendation engine module in this paper is designed and optimized using Spark to implement incremental matrix decomposition on data streams, online collaborative topic model, and improved item-based collaborative filtering algorithm. …”
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Construction of a machine learning-based risk prediction model for depression in middle-aged and elderly patients with cardiovascular metabolic diseases in China: a longitudinal st... by Gege Zhang, Sijie Dong, Li Wang

“…LASSO regression was used to screen for risk factors, and three machine learning algorithms—logistic regression (LR), random forest (RF), and XGBoost—were employed to build predictive models. …”
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Optimization of emergency logistics for urban flooding with consideration of rainfall effects by Peiwen Zhang, Chenxing Zhang, Pan Zhang, Xuxian Yan, Huawei Yang

“…This study proposes a two-stage optimization framework for emergency logistics. First, a supply distribution model is developed by integrating resource scarcity indices and disaster severity indices, optimized through a simulated annealing algorithm. …”
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Construction of a Prediction Model for Sleep Quality in Embryo Repeated Implantation Failure Patients Undergoing Assisted Reproductive Technology Based on Machine Learning: A Singl... by Zhao Y, Xu C, Qin N, Bai L, Wang X, Wang K

“…Yanjun Zhao,1,* Chenying Xu,1,* Ningxin Qin,2,* Lina Bai,1 Xuelu Wang,1 Ke Wang2 1Operating Room, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, People’s Republic of China; 2Reproductive Medicine Center, Shanghai Key Laboratory of Maternal Fetal Medicine, Shanghai Institute of Maternal-Fetal Medicine and Gynecologic Oncology, Shanghai First Maternity and Infant Hospital, School of Medicine, Tongji University, Shanghai, 200092, People’s Republic of China*These authors contributed equally to this workCorrespondence: Xuelu Wang, Email wangxuelu@51mch.com Ke Wang, Email wangkeyfy@126.comObjective: Constructing a predictive model for sleep quality in embryo Repeated Implantation Failure(RIF) patients using multiple machine learning algorithms, verifying its performance, and selecting the optimal model.Methods: Retrospective collection of clinical data from RIF patients who underwent assisted reproductive technology at the Reproductive Medicine Center of Tongji University Affiliated Obstetrics and Gynecology Hospital from January 2022 to June 2022, divided into a training set and a validation set in an 8:2 ratio. …”
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Swarm intelligence for energy-efficient heating, ventilation, and air conditioning (HVAC) systems: A case study in smart buildings by Vinoth Kanna I, Raja Subramani, Maher Ali Rusho, Shubham Sharma, Ramachandran T, Abinash Mahapatro, Deepak Gupta, Jasmina Lozanovic

“…This research utilizes swarm intelligence algorithms—Particle Swarm Optimization (PSO), Ant Colony Optimization (ACO), and hybrid PSO-ACO-to optimize energy efficiency and thermal comfort in smart building HVAC systems. …”
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RELIABILITY ESTIMATION OF MECHANICAL SEALS BASED ON ARTIFICIAL HUMMINGBIRD ALGORITHM AND THREE⁃PARAMETER WEIBULL DISTRIBUTION by LI AnHong, ZHU JunHua, YU Ling

“…In order to quickly and accurately evaluate the reliability of mechanical seals,the three⁃parameter Weibull distribution was used to model the mechanical seal failure data.The reliability evaluation problem of mechanical seal was transformed into a constraint optimization problem,and a reliability evaluation method based on artificial hummingbird algorithm(AHA)was proposed.Through numerical simulation and case analysis,maximum likelihood estimation(MLE),improved Harris Hawks optimization(IHHO)algorithm and AHA were used to compare calculation accuracy and operational efficiency in solving the Weibull distribution parameter estimation problems.The results show that the parameter estimation using AHA has advantages of faster convergence speed and higher accuracy,and it can shorten the optimization time and improve the accuracy compared with MLE algorithm and IHHO algorithm,which provides a new and efficient method for Weibull parameter estimation of mechanical seals.…”
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Classification and spectrum optimization method of grease based on infrared spectrum by Xin Feng, Yanqiu Xia, Peiyuan Xie, Xiaohe Li

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DLE-YOLO: An efficient object detection algorithm with dual-branch lightweight excitation network by Peitao Cheng, Xuanjiao Lei, Haoran Chen, Xiumei Wang

“…Thirdly, the localization loss utilizes SIoU loss to further optimize the accuracy of the bounding box. Our method achieves a mAP value of 46.0% on the MS-COCO dataset, which is a 2% mAP improvement compared to the baseline YOLOv5-m, while bringing a 19.3% reduction in parameter count and a 12.9% decrease in GFLOPs. …”
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Evaluation and Optimization of Air Traffic Complexity Based on Resilience Metrics by Hongyong Wang, Jiawen Huang, Taotao Deng, Ziqi Song

“…By establishing a sector complexity optimization model, the complexity of sector air traffic and its volatility can be greatly reduced by changing the departure time of some flights. …”
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Deep Learning-Based Feature Matching Algorithm for Multi-Beam and Side-Scan Images by Yu Fu, Xiaowen Luo, Xiaoming Qin, Hongyang Wan, Jiaxin Cui, Zepeng Huang

“…It also overcomes challenges, such as large nonlinear differences, significant geometric distortions, and high matching difficulty between the MBES and side-scan images, significantly improving the optimized image matching results. The matching error RMSE has been reduced to within six pixels, enabling the accurate matching of multi-beam and side-scan images.…”
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Cooperative trajectory optimization for multiple connected vehicles at an unsignalized intersection by Hao Yang, Xianyang Li, Duoyang Qiu, Xiaomeng Zhu

“…Through numerical simulation analysis of intersection scenarios including crossroad and roundabout, the results demonstrate that the proposed algorithm can achieve optimal trajectories for multi-vehicle cooperative motion while ensuring safe vehicle operation, which improves the efficiency of future intelligent traffic networks.…”
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Using machine learning techniques to evaluate the impact of future climate change on wheat yields in Xinjiang, China by Xuehui Gao, Jian Liu, Haixia Lin, Tehseen Javed, Feihu Yin, Rui Chen, Yue Wen, Jinzhu Zhang, Kefan Yi, Zhenhua Wang

“…Additionally, the impacts of climate change scenarios on wheat yield were predicted using two emission scenarios (SSP45 and SSP85) from global climate models (GCMs) and machine learning (ML) algorithms. …”
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Optimization of Multiperiod Mixed Train Schedule on High-Speed Railway by Wenliang Zhou, Junli Tian, Jin Qin, Lianbo Deng, TangJian Wei

“…And its heuristic algorithm is designed to optimize the multiperiod mixed train schedule beginning with generating an initial solution by scheduling all types of train type by type and then repeatedly improving their periodic schedules until the objective value cannot be reduced or the iteration number reaches its maximum. …”
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Novel Design and Optimization of Porous Titanium Structure for Mandibular Reconstruction by Renshun Liu, Yuxiong Su, Weifa Yang, Xiaobing Dang, Chunyu Zhang, Ruxu Du, Yong Zhong

“…The design and optimization technique of the porous structure presented in this paper can be used to control peak stress, improve porosity, and fabricate a lightweight scaffold, which provides a potential solution for mandibular reconstruction.…”
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Retrieval Augmented Therapy Suggestion for Molecular Tumor Boards: Algorithmic Development and Validation Study by Eliza Berman, Holly Sundberg Malek, Michael Bitzer, Nisar Malek, Carsten Eickhoff

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TCE-YOLOv5: Lightweight Automatic Driving Object Detection Algorithm Based on YOLOv5 by Han Wang, Zhenwei Yang, Qiaoshou Liu, Qiang Zhang, Honggang Wang

“…Finally, the EIOU loss function is introduced to measure the overlap between the predicted box and the real box more accurately and improve the detection accuracy. The test results of KITTI and CCTSDB2021 public traffic datasets show that compared with the original YOLOv5 model, the improved algorithm reduces the number of parameters by 20%, the calculation amount by 21%, and mAP@0.5 by 1.0%. …”
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