Optimization and Trends in EV Charging Infrastructure: A PCA-Based Systematic Review by Javier Alexander Guerrero-Silva, Jorge Ivan Romero-Gelvez, Andrés Julián Aristizábal, Sebastian Zapata

“…This systematic review analyzes recent research on EV charging network planning, with a particular focus on optimization techniques, machine learning applications, and sustainability integration. …”
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Advanced Machine Learning Approaches for Predicting Machining Performance in Orthogonal Cutting Process by Sabrina Al Bukhari, Salman Pervaiz

“…We investigated the orthogonal cutting process by using machine learning models to predict its performance. …”
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Machine Learning-Driven Dynamic Traffic Steering in 6G: A Novel Path Selection Scheme by Hibatul Azizi Hisyam Ng, Toktam Mahmoodi

“…Artificial Intelligence (AI) and machine learning (ML) are the optimal candidates to support and deliver these aspirations. …”
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Quantum-enhanced beetle swarm optimized ELM for high-dimensional smart grid intrusion detection by Na Cheng, Shuqing Wang, Lihong Zhao, Yan Hu

“…Abstract This study proposes a novel smart grid intrusion detection model, combining a quantum-enhanced beetle swarm optimization algorithm with extreme learning machine (QBOA-ELM), with the aim of improving detection accuracy, efficiency, and robustness. …”
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Machine Learning‐Driven Extraction of Hybrid Compact Models Integrating Neural Networks and Berkeley Short‐Channel Insulated‐Gate Field‐Effect Transistor Model‐Common Multigate for... by Seungjoon Eom, Seunghwan Lee, Hyeok Yun, Kyeongrae Cho, Soomin Kim, Rockhyun Baek

“…This study presents a novel machine learning–based method to accelerate and enhance the accuracy of compact model generation for multiple devices simultaneously. …”
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Transforming Agricultural Productivity with AI-Driven Forecasting: Innovations in Food Security and Supply Chain Optimization by Sambandh Bhusan Dhal, Debashish Kar

“…This review examines how advanced AI-driven forecasting models, including machine learning (ML), deep learning (DL), and time-series forecasting models like SARIMA/ARIMA, are transforming regional agricultural practices and food supply chains. …”
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Privacy-preserving detection and classification of diabetic retinopathy using federated learning with FedDEO optimization by Dasari Bhulakshmi, Dharmendra Singh Rajput

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Engineering a multi model fallback system for edge devices by Gaurav Kadve, Abishi Chowdhury, Vishal Krishna Singh, Amrit Pal

“…The proposed system utilizes a model pool of optimized models and a confidence-based switching mechanism to dynamically select the most reliable model for inference. …”
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The results of using machine learning technology for intraocular lenses optical power calculation by A.A. Arzamastsev, O.L. Fabrikantov, S.V. Belikov, N.A. Zenkova

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Utilizing machine learning and digital twin technology for rock parameter estimation from drilling data by Abdullah Khan, Yiming Li, Muhammad Shoaib, Umair Sajjad, Fuxin Rui

“…The integration of the DT technology with numerical methods, including finite element analysis (FEA) and discrete element model (DEM), facilitates real-time monitoring, simulation, and optimization of rock parameters extracted from drilling, which can enhance accuracy and robustness even with limited empirical data, representing a notable solution. …”
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Optimizing Federated Learning on TinyML Devices for Privacy Protection and Energy Efficiency in IoT Networks by William Villegas-Ch, Rommel Gutierrez, Alexandra Maldonado Navarro, Aracely Mera-Navarrete

“…This study addresses these issues by developing a federated system optimized for Tiny Machine Learning devices, integrating differential privacy and encryption techniques adapted to their constraints. …”
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Incorporating a Deep Neural Network into Moving Horizon Estimation for Embedded Thermal Torque Derating of an Electric Machine by Alexander Winkler, Pranav Shah, Katrin Baumgärtner, Vasu Sharma, David Gordon, Jakob Andert

“…Specifically, a Long Short-Term Memory (LSTM)-based DNN is trained using synthetic data derived from a high-fidelity thermal model of a Permanent Magnet Synchronous Machine (PMSM), applied within a thermal derating torque control strategy for battery electric vehicles. …”
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Explainable Ensemble Learning Model for Residual Strength Forecasting of Defective Pipelines by Hongbo Liu, Xiangzhao Meng

“…Furthermore, the predictive models typically lack interpretability. To address these issues, this study proposes a hybrid prediction model for the residual strength of defective pipelines based on Bayesian optimization (BO) and eXtreme Gradient Boosting (XGBoost). …”
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Prediction and Monitoring Model of Concrete Dam Deformation Based on WOA-RFR by FENG Yu, WU Yunxing, GU Wenjing, PANG Qiong, GU Yanchang, CHEN Siyu

“…The random forest algorithm and whale optimization algorithm were introduced in the construction of the prediction model of concrete dam deformation based on WOA-RFR to improve the prediction accuracy and model performance. …”
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Research on bearing fault diagnosis based on improved northern goshawk algorithm optimizing SVM by WU Xiaojun, LI Quwei

“…An improved northern goshawk optimization (INGO) algorithm was proposed to address the local optimization problem that swarm intelligence algorithms often encounter when optimizing support vector machine (SVM) models, and it was applied to fault diagnosis of rolling bearings. …”
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Research on Pose Error Modeling and Compensation of Posture Adjustment Mechanism Based on WOA-RBF Neural Network by Hongyu Shen, Honggen Zhou, Yiyang Jin, Lei Li, Bo Deng, Jiawei Xu

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Evolutionary approach for composing a thoroughly optimized ensemble of regression neural networks by Lazar Krstic, Milos Ivanovic, Visnja Simic, Boban Stojanovic

“…GeNNsem has been evaluated on two regression benchmark problems and compared with related machine learning techniques. The proposed approach exhibited supremacy over other ensemble approaches and individual neural networks in all common regression modeling metrics. …”
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Integrated multi-task feature learning and interactive active optimization for scene retargeting in preschool educational applications by Suhui Yao, Lan Lv

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Optimized intelligent learning for groundwater quality prediction in diverse aquifers of arid and semi-arid regions of India by Imran Khan, Sarwar Nizam, Apoorva Bamal, Abdul Majed Sajib, Mir Talas Mahammad Diganta, Mohd Azfar Shaida, S.M. Ashekuzzaman, Stephen Nash, Agnieszka I. Olbert, Md Galal Uddin

“…This study evaluates GW resources across the diverse aquifer systems of arid and semi-arid regions of northwest India using the recently developed Root Mean Squared-Water Quality Index (RMS-WQI) model, optimized with machine learning (ML) techniques. …”
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Optimizing Screw Fixation in Total Hip Arthroplasty: A Deep Learning and Finite Element Analysis Approach by Jacob Stroud, Emily T. Yan, Jacob Anthony, Kyle Walker, Chung-Hyun Goh

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