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. …”

Electric Vehicle Cluster and Scheduling Strategy Based on Dynamic Game by LI Shuai, DING Xiying, JIANG Hongfa

“…The upper layer takes the peak shaving demand and peak shaving cost of distribution system operator (DSO) as the optimization objectives, and uses an improved multi-objective particle swarm optimization algorithm to obtain the game strategy set of DSO. …”
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Application of Fuzzy Logic Sliding Mode Control Approach With PID Structure for Electro-Hydraulic Actuator Tracking System by Muhamad Fadli Ghani, Ahmad Athif Mohd Faudzi, Rozaimi Ghazali, Shahrol Mohamaddan

“…The proposed control strategy was designed with the switching function modification based on an FL approach in the conventional SMC algorithm. Due to the difficulty of concurrent hybrid design, a particle swarm optimization (PSO) algorithm was employed to determine the optimal control variables value. …”
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SPECIAL CHARACTERISTICS OF AERODYNAMIC PROPERTIES OF UNMANNED AIRCRAFT WITH THE HIGH-ASPECT-RATIO WING by O. Е. Lukyanov, A. V. Ostrovoy, M. A. Mensez Soto, Y. A. Klimov, V. G. Shakhov

“…The technique is based on numerical multidisciplinary mathematical modeling using the discrete vortex method and the topology optimization algorithm based on the variable density body model. …”
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A typical scenario generation method for renewable energy power systems based on time-sequenced operational simulations by PENG Zhuyi, SONG Shan, XU Sixuan, GU Kanghui, GE Yi, WANG Quanquan, SUN Wentao

“…Firstly， a unit combination model that incorporates AC power flow constraints is constructed， and a two-stage solution strategy based on second-order cone relaxation is adopted to perform 8，760-hour time-sequenced simulations in the multi-period optimal power flow model. …”
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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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A Global Coverage Path Planning Method for Multi-UAV Maritime Surveillance in Complex Obstacle Environments by Yiyuan Li, Weiyi Chen, Bing Fu, Zhonghong Wu, Lingjun Hao

“…Secondly, a method for calculating obstacle-avoidance path costs based on the Voronoi diagram is proposed, laying the foundation for obtaining the optimal access order. Thirdly, an improved discrete grey wolf optimizer (IDGWO) algorithm integrated with variable neighborhood search (VNS) operations is proposed to perform task assignment for multiple UAVs and achieve workload balancing. …”
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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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Development of a postoperative recurrence prediction model for stage Ⅰ non-small cell lung cancer patients using multimodal data based on machine learning by ZHANG Di, WU Yi, XU Yu

“…A combined model was further constructed by integrating both feature sets, and model performance was compared to identify the optimal predictive model.Results‍　‍This study screened the features from non-contrast CT images and ultimately selected 7 radiomic features for constructing radiomic model. …”
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Fuzzy Robust Modification Design of EMU Transmission Gear by Ziqiang Sheng, Yuedong Wang, Xiaoning Bai, Shenxuan Wang

“…On this basis， the fuzzy theory is introduced， the mathematical model of gear modification robust optimization is established based on improved tolerance model， the NSGA-III algorithm is used to find the optimal solution， and the comparison with other modification schemes is completed. …”
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Investigation of Hysteresis Phenomena and Compensation in Piezoelectric Stacks for Active Rotor by Xiancheng Gu, Weidong Yang, Linghua Dong, Jinlong Zhou

“…Subsequently, the Bouc–Wen model is adopted to establish the hysteresis model of the piezoelectric actuator, with its parameters identified through the particle swarm optimization (PSO) algorithm. …”
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The outcome prediction method of football matches by the quantum neural network based on deep learning by Yang Sun, Hongyang Chu

“…During the model training phase, gradient descent is used to optimize weight parameters, and quantum algorithms are integrated to continuously adjust network weights to minimize prediction errors. …”
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Ensemble machine learning prediction accuracy: local vs. global precision and recall for multiclass grade performance of engineering students by Yagyanath Rimal, Yagyanath Rimal, Navneet Sharma

“…The grid search for random forest algorithms achieved a score of 79% when optimally tuned; however, the training accuracy was 99%. …”
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Review of Maglev Train Dynamics Research by WEN Yanfeng, ZHANG Weifeng, CAI Wenfeng, XU Hao

“…Introducing suspension models into UM software can optimize suspension parameters and dynamics indicators, improving train operational stability and safety. …”
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Multilayer perceptron deep learning radiomics model based on Gd-BOPTA MRI to identify vessels encapsulating tumor clusters in hepatocellular carcinoma: a multi-center study by Mengting Gu, Wenjie Zou, Huilin Chen, Ruilin He, Xingyu Zhao, Ningyang Jia, Wanmin Liu, Peijun Wang

“…Compared with the two models aforementioned, the Radiology MLP model demonstrated a 33.4%-131.3% improvement in NRI and a 9.3%-50% improvement in IDI, showing better discrimination, calibration and clinical usefulness in three sets, which was selected as the optimal predictive model. …”
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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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Fuzzy deep learning architecture for cucumber plant disease detection and classification by Anas Bilal, Junaid Ali Khan, Abdulkareem Alzahrani, Khalid Almohammadi, Maha Alamri, Xiaowen Liu

“…At the same time, the ReLU transfer function ensures robustness, mainly when dealing with noisy or incomplete image segments. Feature vector optimization is performed using a chaotic particle swarm algorithm, enhancing the model’s overall accuracy, reliability, and ease of implementation. …”
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Mixed reality infrastructure based on deep learning medical image segmentation and 3D visualization for bone tumors using DCU-Net by Kun Wang, Yong Han, Yuguang Ye, Yusi Chen, Daxin Zhu, Yifeng Huang, Ying Huang, Yijie Chen, Jianshe Shi, Bijiao Ding, Jianlong Huang

“…Conclusion: The deep learning DCU-Net algorithm model can improve the performance of tumor CT image segmentation, and the reconstructed fine model can better reflect the actual situation of individual tumors; the MR system constructed based on this model enhances clinicians’ understanding of tumor morphology and spatial relationships. …”
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Power capacity enhancement of hydropower plant through the penetration of solar and wind energy by Ahmad Shah Irshad, Ahmad Shah Amin, Amir Mohammad Ilham, M.H. Elkholy, Said Elias, Tomonobu Senjyu

“…A multi-objective genetic algorithm was employed to optimize this integration, addressing objectives such as maximizing power output, improving energy efficiency, and minimizing environmental impact. …”
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Distribution Network Topology Identification Based on Finite Key Nodes and Wasserstein Distance by Yao ZHAO, Yongjiang CHEN, Kunhua JI, Yun WANG

“…Firstly, the finite key nodes can be used to identify the topology when the subspace perturbation model is used to prove the topology change of the distribution network, and the concept of influence degree is introduced through the entropy method based hybrid K-Shell algorithm and the importance of nodes is obtained by the influence degree and the electrical distance between the nodes, thus determining the key nodes in the distribution network topology. …”
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