Laser–Arc Welding Adaptive Model of Multi-Pre-Welding Condition Based on GA-BP Neural Network by Zesheng Wu, Zhaodong Zhang, Gang Song

“…In this study, laser–arc hybrid welding is used to perform butt welding on 6 mm Q345 steel in various assembly conditions, and we propose an adaptive model of the BP neural network optimized by a genetic algorithm (GA) for laser–arc welding. …”
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Physics-based modeling and mechanism of polycrystalline diamond tool wear in milling of 70 vol% Si/Al composite by Lianjia Xin, Guolong Zhao, Zhiwen Nian, Haotian Yang, Liang Li, Ning He

“…The research findings also offer key insights for optimizing tool selection and machining parameters, advancing both the theoretical understanding and practical application of PCD tool wear.…”
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Computational Methods, Artificial Intelligence, Modeling, and Simulation Applications in Green Hydrogen Production Through Water Electrolysis: A Review by Ahmed Y. Shash, Noha M. Abdeltawab, Doaa M. Hassan, Mohamed Darweesh, Y. G. Hegazy

“…This review focuses on the role of computational approaches and artificial intelligence (AI) in optimizing green hydrogen technologies. Key approaches to improving electrolyzer efficiency and scalability include computational fluid dynamics (CFD), thermodynamic modeling, and machine learning (ML). …”
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A Novel High-Precision Workpiece Self-Positioning Method for Improving the Convergence Ratio of Optical Components in Magnetorheological Finishing by Yiang Zhang, Pengxiang Wang, Chaoliang Guan, Meng Liu, Xiaoqiang Peng, Hao Hu

“…Further, based on these thresholds, a hybrid self-positioning method combining machine vision and a probing module is proposed. A composite data acquisition method using both a camera and probe is designed, and a stepwise global optimization model is constructed by integrating a synchronous iterative localization algorithm with the Non-dominated Sorting Genetic Algorithm II (NSGA-II). …”
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Investigation of ML algorithms for prediction of CFD data of fluid flow inside a packed-bed reactor by Yujiang Qiu, Pinxiao Liu

“…Hyper-parameter optimization was conducted employing Sequential Model-Based Optimization (SMBO) considering K-fold as the objective metric to optimize models. …”
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Advanced thermal management in X-ray systems using magnetohydrodynamic nanofluids and Cattaneo-Christov heat flux model by Maryam Johari, Hossein Ali Hoshyar, Esmail Dabirian, Davood Domiri Ganji

“…Abstract This research explores the utilization of magnetohydrodynamic nanofluids to enhance thermal control in high-energy systems, such as X-ray devices, where efficient heat dissipation is essential for optimal performance and lifespan. By integrating analytical and numerical approaches, the study examines heat transfer in nanofluids confined between parallel plates, incorporating thermal radiation and the Cattaneo-Christov heat flux model. …”
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Study on risk factors of impaired fasting glucose and development of a prediction model based on Extreme Gradient Boosting algorithm by Qiyuan Cui, Jianhong Pu, Wei Li, Yun Zheng, Jiaxi Lin, Lu Liu, Peng Xue, Jinzhou Zhu, Mingqing He

“…Feature selection, parameter optimization, and model construction were performed in the training set, while the validation set was used to evaluate the predictive performance of the models. …”
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From Envelope Spectra to Bearing Remaining Useful Life: An Intelligent Vibration-Based Prediction Model with Quantified Uncertainty by Haobin Wen, Long Zhang, Jyoti K. Sinha

“…Bearings are pivotal components of rotating machines where any defects could propagate and trigger systematic failures. …”
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Hybrid Transformer-Based Large Language Models for Word Sense Disambiguation in the Low-Resource Sesotho sa Leboa Language by Hlaudi Daniel Masethe, Mosima Anna Masethe, Sunday O. Ojo, Pius A. Owolawi, Fausto Giunchiglia

“…The enhanced results explored optimization techniques and hybrid model architectures to improve performance. …”
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HSDT-TabNet: A Dual-Path Deep Learning Model for Severity Grading of Soybean Frogeye Leaf Spot by Xiaoming Li, Yang Zhou, Yongguang Li, Shiqi Wang, Wenxue Bian, Hongmin Sun

“…Furthermore, the overall generalization ability of the model is improved through hyperparameter optimization based on the tree-structured Parzen estimator (TPE). …”
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Research on computer multi feature fusion SVM model based on remote sensing image recognition and low energy system by Yangming Wu, Hao Wu, Xin Tang, Jianwei Lv, Rufei Zhang

“…Therefore, this paper aims to explore a low-energy multi-feature fusion support vector machine (SVM) model based on remote sensing image recognition. …”
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Crushing Force Prediction Method of Controlled-Release Fertilizer Based on Particle Phenotype by Linlin Sun, Xiubo Chen, Zixu Chen, Linlong Jing, Jinxing Wang, Xinpeng Cao, Shenghui Fu, Yuanmao Jiang, Hongjian Zhang

“…A particle swarm optimization–support vector machine (PSO-SVM) model was then developed to predict the crushing force based on fertilizer shape features. …”
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Multi-strategy enhanced marine predator algorithm: performance investigation and application in intrusion detection by Zhongmin Wang, Yujun Zhang, Jun Yu, YuanYuan Gao, Guangwei Zhao, Essam H. Houssein, Rui Zhong

“…Finally, we extend the proposed MEMPA to optimize the hyper-parameters of the Extreme Learning Machine (ELM) for intrusion detection, and the performance of MEMPA-ELM increases the average accuracy by 0.79% than the second-best model. …”
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AI-Based Identification and Redevelopment Prioritization of Inefficient Industrial Land Using Street View Imagery and Multi-Criteria Modeling by Yan Yu, Qiqi Yan, Yu Guo, Chenhe Zhang, Zhixiang Huang, Liangze Lin

“…On this basis, a redevelopment potential evaluation index system is constructed based on the necessity, maturity, and urgency of redevelopment, and the Particle Swarm Optimization-Projection Pursuit (PSO-PP) model is introduced to objectively evaluate redevelopment potential by adaptively reducing the reliance on expert judgment. …”
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IoT-driven smart assistive communication system for the hearing impaired with hybrid deep learning models for sign language recognition by Mashael Maashi, Huda G. Iskandar, Mohammed Rizwanullah

“…Furthermore, the improved MobileNetV3 model is employed for the feature extraction process. …”
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Research on recycling value grading and real-time perception of rock debris from TBM tunneling by Weiqi Yue, Weilin Su, Zhanfei Gu, Xiao Qu

“…Notably, the hyperparameter optimization significantly enhances the accuracy of the ANN perception model. …”
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A Data-Driven Monitoring System for a Prescriptive Maintenance Approach: Supporting Reinforcement Learning Strategies by Joaquín Ordieres-Meré, Antonio Sánchez-Herguedas, Ángel Mena-Nieto

“…A bearing temperature sensitivity analysis was conducted based on the coefficients obtained from the optimization of the regression model. To fully exploit the capabilities of these techniques for application in this field, we designed a reference framework intended to foster model deployment in an industrial context by promoting the self-monitoring and updating of the models when required. …”
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Transient Stability Analysis of Wind-Integrated Power Systems via a Kuramoto-like Model Incorporating Node Importance by Min Cheng, Jiawei Yu, Mingkang Wu, Yayao Zhang, Yihua Zhu, Yuanfu Zhu

“…In addition, the Kron method is applied to simplify the power grid model, constructing a hybrid Kuramoto-like model that integrates second-order synchronous machine oscillators and first-order wind power oscillators. …”
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Is Artificial Intelligence a Game-Changer in Steering E-Business into the Future? Uncovering Latent Topics with Probabilistic Generative Models by Simona-Vasilica Oprea, Adela Bâra

“…Topic 2 (28.1%) explores AI and Machine Learning (ML) in web-based business, emphasizing customer service, innovation and workflow optimization. …”
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Systematic Literature Review: Analisa Sentimen Masyarakat terhadap Penerapan Peraturan ETLE by Syafrial Fachri Pane, Muhammad Syiarul Amrullah

“…Therefore, the model for analyzing public sentiment regarding the application of ETLE regulations can be an option for hybrid methods, multi-task learning, deep learning, machine learning, and the XGBoost model to obtain superior performance with preprocessing data stages, handling imbalanced data and optimization models. …”
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