CNN Based Fault Classification and Predition of 33kw Solar PV System with IoT Based Smart Data Collection Setup by K. Punitha, G. Sivapriya, T. Jayachitra

“…By detecting and addressing faults early, systems can maintain optimal performance levels. Machine Learning (ML) in Solar Photovoltaic (PV) systems refers to the application of algorithms and statistical models that enable computers to perform specific tasks without using explicit instructions, relying instead on patterns and inference. …”
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Data Analysis and Forecasting of COVID-19 Pandemic in Kuwait Based on Daily Observation and Basic Reproduction Number Dynamics by Kayode Oshinubi, Fahima Al-Awadhi, Mustapha Rachdi, Jacques Demongeot

“…Forecasting has been done using ARIMA model, Exponential smoothing model, Holt’s method, Prophet forecasting model and machine learning models like log-linear, polynomial and support vector regressions. …”
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Internet of Things-Cloud Control of a Robotic Cell Based on Inverse Kinematics, Hardware-in-the-Loop, Digital Twin, and Industry 4.0/5.0 by Dan Ionescu, Adrian Filipescu, Georgian Simion, Adriana Filipescu

“…Additionally, it provides communication interfaces via PROFINET IO to SCADA and Human Machine Interface (HMI), and through Open Platform Communication—Unified Architecture (OPC-UA) for Siemens NX-MCD with DT virtual model. …”
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Scaling photonic systems-on-chip production with neural networks by Yadav Ksenia, Bidnyk Serge, Balakrishnan Ashok

“…We adopt multi-path neural network architectures to reduce the computational requirements of model training and to mitigate the risk of overfitting. …”
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Monitoring and Prediction of the Real-Time Transient Thermal Mechanical Behaviors of a Motorized Spindle Tool by Tria Mariz Arief, Wei-Zhu Lin, Jui-Pin Hung, Muhamad Aditya Royandi, Yu-Jhang Chen

“…The spindle is a critical component that significantly influences the performance of machine tools. In motorized spindles, heat generation from both the bearings and built-in motor leads to thermal deformation of structural components, which, in turn, affects machining accuracy. …”
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Neural-Network-Based Prediction of Non-Burial Overwintering Material Covering Height for Wine Grapes by Yunlong Ma, Jinyue Yang, Yibo Chen, Ping Wang, Qinming Sun

“…The model predicted optimal insulation heights of 6 cm for the tarpaulin and 22 cm for the insulation blanket. …”
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Product collaborative filtering based recommendation systems for large-scale E-commerce by Trang Trinh, Van-Ho Nguyen, Nghia Nguyen, Duy-Nghia Nguyen

“…Future work will focus on applying multi-model to enhance the accuracy of prediction and configuration to optimize the cost of cluster operations.…”
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On the use of deep learning for computer-generated holography by Xuan Yu, Haomiao Zhang, Zhe Zhao, Xuhao Fan, Shaodong Hu, Zongjing Li, Wenbin Chen, Daqian Li, Shaoxi Shi, Wei Xiong, Hui Gao

“…Summary: The research disciplines of computer-generated holography (CGH) and machine learning have evolved in parallel for decades and experienced booming growth due to breakthroughs in mathematical optimization and computing hardware. …”
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A Methodology for Electricity Demand Forecasting Using a Hybrid Approach by Fanidhar Dewangan, Monalisa Biswal, Nand Kishor

“…The primary objective of LF is to establish an optimal load model for the power grid, conducted offline, to achieve accurate predictions, thereby minimizing operational costs and enhancing grid stability. …”
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A novel adaptive safe semi-supervised learning framework for pattern extraction and classification by Jun Ma, Junjie Li, Jiachen Sun

“…The framework implements the weight assignment of the self-similarity graph during the model learning process. In order to adapt to the learning needs, accelerate the learning speed, and avoid the impact of the curse of dimensionality, the framework also optimizes the features of each sample point through an automatic weighting mechanism to extract effective features and eliminate redundant information in the learning task. …”
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Method of continuous generation grinding tooth surface modification based on electronic gearbox superimposed high-order motion by HAN Jiang, RUI Xiaoyu, TIAN Xiaoqing, YOU Tongfei, LI Guanghui, XIA Lian

“…Then, a continuous generative grinding machining model was established based on the parameter equation of the worm wheel gear surface and the linkage relation with the electronic gearbox. …”
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Customer segmentation in the digital marketing using a Q-learning based differential evolution algorithm integrated with K-means clustering. by Guanqun Wang

“…Furthermore, four widely recognized machine learning methods are employed to classify the clustering results, achieving over 95% classification accuracy on the test set. …”
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Efficient Approach for Brain Tumor Detection and Classification Using Fuzzy Thresholding and Deep Learning Algorithms by Nashaat M. Hussain Hassan, Wadii Boulila

“…In the second stage, an optimized convolutional neural network (CNN) model classifies tumors into four categories: glioma, meningioma, pituitary tumor, and no tumor. …”
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RRMSE-enhanced weighted voting regressor for improved ensemble regression. by Shikun Chen, Wenlong Zheng

“…This uniform weighting approach doesn't consider that some models may perform better than others on different datasets, leaving room for improvement in optimizing ensemble performance. …”
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Deep Learning-Enhanced Spectrogram Analysis for Anatomical Region Classification in Biomedical Signals by Abdul Karim, Semin Ryu, In cheol Jeong

“…Spectrograms derived from palpation and percussion signals were preprocessed into grayscale images and optimized through data augmentation and hyperparameter tuning to enhance the model’s generalization. …”
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Enhancing Power Converter Reliability Through a Logistic Regression-Based Non-Invasive Fault Diagnosis Technique by Acácio M. R. Amaral

“…The solution presented in this article combines signal processing techniques (SPTs) with a machine learning (ML) algorithm to determine the optimal time for capacitor replacement. …”
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Bank Customer Segmentation and Marketing Strategies Based on Improved DBSCAN Algorithm by Xiaohua Yan, Yufeng Li, Fuquan Nie, Rui Li

“…The model is then applied in a real-world scenario, leading to an average business revenue growth rate of 16.08% and a 4.5% increase in customer engagement.…”
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Identification of Anomaly Detection in Power System State Estimation Based on Fuzzy C-Means Algorithm by Di Leng, Ziliang Qiu

“…On this basis, the power system state estimation model established by particle swarm optimization support vector machines is used to judge the operational state of the power system. …”
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DeepATsers: a deep learning framework for one-pot SERS biosensor to detect SARS-CoV-2 virus by Ankhbayar Nyamdavaa, Kiran Kaladharan, Erdene-Ochir Ganbold, Seungdo Jeong, Seonuck Paek, Yansen Su, Fan-Gang Tseng, Tseren-Onolt Ishdorj

“…This significantly improves the average accuracy of protein classification from 0.6000 to 0.9750. The deep learning model deployed optimal hyperparameters and outperformed in most measurements comparing supervised machine learning methods such as RF, GBM, SVM, and KNN, both with and without augmented spectral datasets. …”
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Deteksi Berita Hoaks Berbahasa Indonesia Menggunakan One-Dimensional Convolutional Neural Network by Muhammad Zuama Al Amin, Muhammad Ariful Furqon, Dwi Wijonarko

“…Model dilatih menggunakan optimizer Adam dan evaluasi kinerja menggunakan 10-fold cross-validation. …”
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