Accelerated Modeling of Transients in Electromagnetic Devices Based on Magnetoelectric Substitution Circuits by Sergii Tykhovod, Ihor Orlovskyi

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Enhanced Modulated Model Predictive Control for Matrix Converters in Overmodulation Zones by Ali Sarajian, Quanxue Guan, Ibrahim Harbi, Davood Arab Khaburi, Ralph Kennel, Cristian Garcia, Patrick Wheeler, Jose Rodriguez

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Voltage Quality Enhancement of Low-Voltage Smart Distribution System Using Robust and Optimized DVR Controllers: Application of the Harris Hawks Algorithm by Mohamed Metwally Mahmoud, Yahia M. Esmail, Basiony Shehata Atia, Omar Makram Kamel, Kareem M. AboRas, Mohit Bajaj, Syed Sabir Hussain Bukhari, Daniel Eutyche Mbadjoun Wapet

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Machine Learning-Based Prediction of Feed Conversion Ratio: A Feasibility Study of Using Short-Term FCR Data for Long-Term Feed Conversion Ratio (FCR) Prediction by Xidi Yang, Liangyu Zhu, Wenyu Jiang, Yiting Yang, Mailin Gan, Linyuan Shen, Li Zhu

“…This study explores the feasibility of predicting long-term FCR using short-term FCR data based on machine learning techniques. We employed nineteen machine learning algorithms, including Linear Regression, support vector machines (SVMs), and Gradient Boosting, using historical datasets to train and validate the models. …”
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Construction of Graduate Behavior Dynamic Model Based on Dynamic Decision Tree Algorithm by Fen Yang

“…Incremental adaptive optimization of the traditional decision tree model can significantly improve the prediction effect and prediction time of dynamic data and provide theoretical support for the industrialization and social significance of big data technology. …”
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Fall Risk Prediction Using Instrumented Footwear in Institutionalized Older Adults by Huanghe Zhang, Chuanyan Wu, Yulong Huang, Rui Song, Damiano Zanotto, Sunil K. Agrawal

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Exploring prospects, hurdles, and road ahead for generative artificial intelligence in orthopedic education and training by Nikhil Gupta, Kavin Khatri, Yogender Malik, Amit Lakhani, Abhinav Kanwal, Sameer Aggarwal, Anshul Dahuja

“…Future research should focus on addressing these challenges through ongoing research, optimizing generative AI models for medical content, exploring best practices for ethical AI usage, curriculum integration and evaluating the long-term impact of these technologies on learning outcomes. …”
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Capacity Management as a Service for Enterprise Standard Software by Hendrik Müller, Sascha Bosse, Klaus Turowski

“…We argue that utilized historical workload traces often contain a variety of performance-related information that allows for the integration of performance prediction techniques through machine learning. Since enterprise applications excessively make use of standard software that is shipped by large software vendors to a wide range of customers, standardized prediction models can be trained and provisioned as part of a capacity management service which we propose in this article. …”
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Intelligence model-driven multi-stress adaptive reliability enhancement testing technology by Shouqing Huang, Beichen He, Jing Wang, Xiaoyang Li, Rui Kang, Fangyong Li

“…Case study verification shows that IMD-MSARET outperforms traditional methods, such as simple random testing and orthogonal testing, in terms of test efficiency, prediction accuracy, and test item consumption. The TSO-GPR model-driven IMD-MSARET is superior to GPR, TSO-SVM, support vector machine and Tuna Swarm Optimization–Backpropagation Neural Network (TSO-BPNN) in terms of accuracy, efficiency, and test item cost for constructing multi-stress limit envelopes.…”
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Recovering 3D Basin Basement Relief Using High-Precision Magnetic Data Through Particle Swarm Optimization and Back Propagation Algorithm by Shen Yan, Xinjun Zhang, Zhongda Shang, Kai Wang, Yixin Ma

“…This paper proposes a new method for the inversion of magnetic basement interfaces using a particle swarm optimization algorithm that combines potential field processing and machine learning techniques. …”
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An UWB LNA Design with PSO Using Support Vector Microstrip Line Model by Salih Demirel, Filiz Gunes, A. Kenan Keskin

“…After the determination of the termination impedance, to provide this impedance with IMC and OMC, dimensions of microstrip lines are obtained with simple, derivative-free, easily implemented algorithm Particle Swarm Optimization (PSO). In the optimization of matching circuits, highly accurate and fast SVRM model of microstrip line is used instead of analytical formulations. …”
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MetaStackD A robust meta learning based deep ensemble model for prediction of sensors battery life in IoE environment by D. Gayathri, S. P. Shantharajah

“…Abstract Advancements in Artificial Intelligence, Machine Learning, and Deep Learning have paved the way for ample applications in real-time. …”
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Optimization of Vertical Ultrasonic Attenuator Parameters for Reducing Exhaust Gas Smoke of Compression–Ignition Engines: Efficient Selection of Emitter Power, Number, and Spacing... by Adil Kadyrov, Łukasz Warguła, Aliya Kukesheva, Yermek Dyssenbaev, Piotr Kaczmarzyk, Wojciech Klapsa, Bartosz Wieczorek

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Vibration Tendency Prediction Approach for Hydropower Generator Fused with Multiscale Dominant Ingredient Chaotic Analysis, Adaptive Mutation Grey Wolf Optimizer, and KELM by Wenlong Fu, Kai Wang, Jiawen Tan, Kaixuan Shao

“…For this purpose, a novel hybrid approach combined with multiscale dominant ingredient chaotic analysis, kernel extreme learning machine (KELM), and adaptive mutation grey wolf optimizer (AMGWO) is proposed. …”
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Ensemble Learning for Spatial Modeling of Icing Fields from Multi-Source Remote Sensing Data by Shaohui Zhou, Zhiqiu Gao, Bo Gong, Hourong Zhang, Haipeng Zhang, Jinqiang He, Xingya Xi

“…Additionally, we employed the SHAP model to provide a physical interpretation of the stacking model, confirming the independence of selected features. …”
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Prediction of Pile Bearing Capacity Using Opposition-Based Differential Flower Pollination-Optimized Least Squares Support Vector Regression (ODFP-LSSVR) by Nhat-Duc Hoang, Xuan-Linh Tran, Thanh-Canh Huynh

“…This study proposes a data-driven model for coping with the problem of interest that hybridizes machine learning and metaheuristic approaches. …”
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Spike Stall Precursor Detection in a Single-Stage Axial Compressor: A Data-Driven Dynamic Modeling Approach by Anish Thapa, Jichao Li, Marco P. Schoen

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Prediction Method for Mechanical Characteristic Parameters of Weak Components of 110 kV Transmission Tower under Ice-Covered Condition Based on Finite Element Simulation and Machin... by Lin Yang, Lulu Mei, Yifei Chen, Yanpeng Hao, Licheng Li, Jianrong Wu, Xianyin Mao

“…The FEM of the 110 kV transmission tower is used to obtain input and output datasets. Thirdly, five machine learning algorithms are considered to establish the prediction models for mechanical characteristic parameters of weak components, and the optimal prediction model is obtained. …”
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Integrated Neural Network Analysis of Machining Characteristics in Dry-Turned Al7075/FA0.9SiC0.9 Hybrid Composite Using PCD Inserts by Sunil Setia, Jarnail Singh, Sant Ram Chauhan, Nikunj Rachchh, Raman Kumar, Abhijit Bhowmik

“…These findings confirm the model’s reliability in forecasting machining behavior, offering valuable insights for optimizing the dry machining of hybrid composites.…”
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Application of a Hybrid Model Based on CEEMDAN and IMSA in Water Quality Prediction by GUO Li-jin, WU Hao-tian

“…Then, an Improved Mantis Search Algorithm (IMSA) optimized three distinct models: Bidirectional Long Short-Term Memory (BiLSTM) for high-complexity components, Least Squares Support Vector Regression (LSSVR) for medium-complexity components, and Extreme Learning Machine (ELM) for low-complexity components. …”
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