Use Cases of Machine Learning in Queueing Theory Based on a <i>GI</i>/<i>G</i>/<i>K</i> System by Dmitry Efrosinin, Vladimir Vishnevsky, Natalia Stepanova, Janos Sztrik

“…Machine learning (ML) in queueing theory combines the predictive and optimization capabilities of ML with the analytical frameworks of queueing models to improve performance in systems such as telecommunications, manufacturing, and service industries. …”
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Quantum AI: A Cognitive Machine Learning Technique based on Nurturing Food Security Sustainability Predictive Analysis for Life Science - Bioengineering in Healthcare by Senthil G.A., Monica K.M., Prabha R., Prinslin L., Elavarasi R.

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Analyzing Student Graduation and Dropout Patterns Using Artificial Intelligence and Survival Strategies by Behrouz Alefy, Vahid Babazadeh

“…From the careful investigation of the convergence curves obtained from the improved models, the study showed that the Cat Boost Classifier modified with the Weevil Damage Optimization Algorithm (CAWD) model was the best among all with an amazing accuracy of 0.993 after 140 iterations. …”
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Prediction of formation pressure in underground gas storage based on data-driven method by SUI Gulei, FU Yujiang, ZHU Hongxiang, LI Zunzhao, WANG Xiaolin

“…Introducing the proportion of gas injection-production to screen pressure monitoring wells can improve the predictive performance of the data-driven model. …”
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Study on Predicting Blueberry Hardness from Images for Adjusting Mechanical Gripper Force by Hao Yin, Wenxin Li, Han Wang, Yuhuan Li, Jiang Liu, Baogang Li

“…The radial basis network optimized by the chimpanzee optimization algorithm (ChOA-RBF) model was compared with a non-optimized model, and the results showed that the ChOA-RBF prediction model has significant advantages in predicting fruit hardness. …”
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Design and performance analysis of wear-resistant micro-groove cutting tool: Numerical simulation and experimental study by Feilong Du, Fukuan Chen, Tao Zhou, Hongfei Yao, Xuefeng Zhao, Dongwei Zhu, Lin He

“…ML algorithms were employed to develop predictive surrogate models, subsequently driving GA optimization of critical geometric parameters. …”
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Data‐sharing strategies in medical consortium based on master‐slave multichain and federated learning by Bohan Kang, Ning Zhang, Jianming Zhu

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Adverse childhood experiences: terms, concepts, and study methods by Diana S. Shumskaia, Anna V. Trusova, Alexander O. Kibitov

“…However, to date, there is no unique and universally accepted approach to assessment of ACE, which may lead to controversy and low reproducibility of results.The purpose of this review is to examine and compare various methods of assessing and interpreting of ACE in order to identify optimal research algorithms within the current interpretation of the biopsychosocial model in psychiatry.This article reviews current terms, concepts, and methods of studying ACE. …”
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Quantifying ruminal health: A statistical review and application of area and time under the curve in animal science by Luis O. Tedeschi

“…These insights allow researchers and practitioners to evaluate feeding strategies, diagnose metabolic disorders, and optimize animal management practices. AUC-based metrics, supported by the ATAUC algorithm, enable scalable and pragmatic solutions for real-time monitoring and decision-making. …”
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Accurate GRACE terrestrial water storage estimations via a new fusion method by Min Dai, Hao Zhou, Wenjing Ma, Shuyun Zheng, Mingyang Xia, Yaozong Li, Zhicai Luo

“…Urgently addressing this issue by optimizing different products with rigorous algorithms is crucial to enhance the comprehension of global and regional TWS variability. …”
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Multi-objective artificial-intelligence-based parameter tuning of antennas using variable-fidelity machine learning by Slawomir Koziel, Anna Pietrenko-Dabrowska, Stanislaw Szczepanski

“…Due to the reliance on computationally-expensive electromagnetic (EM) simulations, the use of conventional algorithms is prohibitive. These costs can be reduced by appropriate algorithmic tools involving surrogate modeling and soft computing methods. …”
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An Integrated Approach to the Determination of Wages of Bank Employees by Alexander S. Artamonov

“…The integrated approach that was used to calculate the wages of employees of the bank employees taking into account the proposed comparison algorithm with market data on wages submitted by the consulting companies, may potentially contribute to improving the competitiveness of HR-brand of the organization and optimize the size of the wage fund.…”
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A Review of Embodied Grasping by Jianghao Sun, Pengjun Mao, Lingju Kong, Jun Wang

“…In reinforcement learning, the pre-trained model is used to obtain the optimal reward function, which improves the learning efficiency and ability of reinforcement learning; (3) embodied agent: The pre-trained model adopts hierarchical or holistic execution to achieve end-to-end robot control. …”
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Capacity Estimation and Knee Point Prediction Using Electrochemical Impedance Spectroscopy for Lithium Metal Battery Degradation via Machine Learning by Qianli Si, Shoichi Matsuda, Yasunobu Ando, Toshiyuki Momma, Yoshitaka Tateyama

“…To reduce data complexity and improve model efficiency, the input by selecting specific frequency points based on SHAP values is further optimized. …”
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An Analysis of the Design and Kinematic Characteristics of an Octopedic Land–Air Bionic Robot by Jianwei Zhao, Jiaping Gao, Mingsong Bao, Hao Zhai, Xu Pei, Zheng Jiang

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Fault reconfiguration control strategy of islanded marine ranching power supply system based on deep reinforcement learning by Yichun Wang, Bo Zhang, Rongjie Wang, Jiang Desong, Yabo Cui, Zhouyang Sun, Hao Liu

“…To enhance convergence efficiency and generalization capability of the algorithm, noise networks are used to improve exploration ability of dueling DQN algorithm by implementing linear layers with learnable noise using an adaptive noise model. …”
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Path Planning and Motion Control of Robot Dog Through Rough Terrain Based on Vision Navigation by Tianxiang Chen, Yipeng Huangfu, Sutthiphong Srigrarom, Boo Cheong Khoo

“…A significant innovation is the customization of the EGO-Planner to optimize trajectory planning in dynamically changing terrains, coupled with the implementation of a multi-body dynamics model that significantly improves the robot’s stability and maneuverability across various surfaces. …”
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CMDMamba: dual-layer Mamba architecture with dual convolutional feed-forward networks for efficient financial time series forecasting by Zhenkai Qin, Zhenkai Qin, Zhenkai Qin, Baozhong Wei, Baozhong Wei, Yujia Zhai, Ziqian Lin, Xiaochuan Yu, Xiaochuan Yu, Jingxuan Jiang

“…By doing so, it provides more accurate time series modeling, optimizes algorithmic trading strategies, and facilitates investment portfolio risk warnings.ResultsExperiments conducted on four real-world financial datasets demonstrate that CMDMamba achieves a 10.4% improvement in prediction accuracy for multivariate forecasting tasks compared to state-of-the-art models.DiscussionMoreover, CMDMamba excels in both predictive accuracy and computational efficiency, setting a new benchmark in the field of financial time series forecasting.…”
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Digital Reconstruction Method for Low-Illumination Road Traffic Accident Scenes Using UAV and Auxiliary Equipment by Xinyi Zhang, Zhiwei Guan, Xiaofeng Liu, Zejiang Zhang

“…Subsequently, the collected point cloud data are processed with a multiscale voxel iteration method for down-sampling to determine optimal parameters. Then, the improved normal distributions transform (NDT) algorithm and different filtering algorithms are adopted to register the ground and air point clouds, and the optimal combination of algorithms is selected, thus, to reconstruct a high-precision 3D point cloud model of the accident scene. …”
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BIM and AI Integration for Dynamic Schedule Management: A Practical Framework and Case Study by Heap-Yih Chong, Xinyi Yang, Cheng Siew Goh, Yan Luo

“…This study addresses this challenge by proposing a dynamic optimization framework that integrates Building Information Modeling (BIM) and Artificial Intelligence (AI) to enhance schedule management. …”
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