Analysis of Gas Pipeline Failure Factors Based on the Novel Bayesian Network by Machine Learning Optimization by Shuangqing Chen, Shun Zhou, Zhe Xu, Yongbin Liu, Bing Guan, Xiaoyu Jiang, Wencheng Li

“…Secondly, by establishing a neural network model, the value of the CPT of the Bayesian network is determined. …”
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Impact of lens autofluorescence and opacification on retinal imaging by Frank G Holz, Maximilian Pfau, Monika Fleckenstein, Raffael Liegl, Geena C Rennen, Marc Vaisband, Jan Hasenauer

“…A regression model for predicting image quality was developed using a convolutional neural network (CNN). Correlation analysis was conducted to assess the association of lens scores, with retinal image quality derived from human or CNN annotations.Results Retinal image quality was generally high across all imaging modalities (IR (8.25±1.99) >GAF >BAF (6.6±3.13)). …”
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Research on water and fertilizer irrigation system of tea plantation by Xuetao Jia, Ying Huang, Yanhua Wang, Daozong Sun

“…The principal component factor is extracted and input into the back propagation neural network to judge the quality of the tea. The number of principal component factors of image information and spectral information is set to six and three; the overall recognition rate reached 97.8%. …”
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Hybrid Modeling of an Induction Machine to Support Bearing Diagnostics by Praneet Amitabh, Dimitar Bozalakov, Frederik De Belie

“…Finally, the difference in the responses is reduced using the neural network such that it can mimic real-world machine behavior closely. …”
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Enhanced Disc Herniation Classification Using Grey Wolf Optimization Based on Hybrid Feature Extraction and Deep Learning Methods by Yasemin Sarı, Nesrin Aydın Atasoy

“…The proposed approach begins with feature extraction using ResNet50, a deep convolutional neural network known for its robust feature representation capabilities. …”
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Analysis of Feature Extraction and Anti-Interference of Face Image under Deep Reconstruction Network Algorithm by Jin Yang, Yuxuan Zhao, Shihao Yang, Xinxin Kang, Xinyan Cao, Xixin Cao

“…To explore the anti-interference performance of convolutional neural network (CNN) reconstructed by deep learning (DL) framework in face image feature extraction (FE) and recognition, in the paper, first, the inception structure in the GoogleNet network and the residual error in the ResNet network structure are combined to construct a new deep reconstruction network algorithm, with the random gradient descent (SGD) and triplet loss functions as the model optimizer and classifier, respectively, and it is applied to the face recognition in Labeled Faces in the Wild (LFW) face database. …”
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Violence Detection From Industrial Surveillance Videos Using Deep Learning by Hamza Khan, Xiaohong Yuan, Letu Qingge, Kaushik Roy

“…The lightweight convolutional neural network (CNN) model initially identifies individuals in the video stream to minimize the processing of irrelevant frames. …”
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Evaluating GRU Algorithm and Double Moving Average for Predicting USDT Prices: A Case Study 2017-2024 by RAHMAT, Munirul ula, Zara Yunizar

“…GRU, a deep learning-based recurrent neural network, processes sequential data using a gating mechanism, making it effective for capturing short-term price dynamics. …”
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From non-human to human primates: a translational approach to enhancing resection, safety, and indications in glioma surgery while preserving sensorimotor abilities by Matteo Gambaretti, Matteo Gambaretti, Luca Viganò, Luca Viganò, Matteo Gallo, Giovanni Pratelli, Tommaso Sciortino, Lorenzo Gay, Marco Conti Nibali, Alberto Luigi Gallotti, Alberto Luigi Gallotti, Leonardo Tariciotti, Luca Mattioli, Lorenzo Bello, Lorenzo Bello, Gabriella Cerri, Gabriella Cerri, Marco Rossi, Marco Rossi, Marco Rossi

“…The main goal, and, at the same time, the main challenge, of oncological neurological surgery is to avoid permanent neurological deficit while reaching maximal resection, particularly when the tumor infiltrates the neural network subserving motor functions. Brain mapping techniques were developed using neurophysiological probes to identify the areas and tracts subserving sensorimotor function, ensuring their preservation during the resection. …”
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Correction of CAMS PM₁₀ Reanalysis Improves AI-Based Dust Event Forecast by Ron Sarafian, Sagi Nathan, Dori Nissenbaum, Salman Khan, Yinon Rudich

“…To evaluate the contribution, we train a deep neural network to predict city-scale dust events (0–72 h) over the Balkans using PM₁₀ fields. …”
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Predictive model of acute kidney injury in critically ill patients with acute pancreatitis: a machine learning approach using the MIMIC-IV database by Shengwei Lin, Wenbin Lu, Ting Wang, Ying Wang, Xueqian Leng, Lidan Chi, Peipei Jin, Jinjun Bian

“…Model construction involved an ensemble of ML, including random forest (RF), support vector machine (SVM), k-nearest neighbors (KNN), naive Bayes (NB), neural network (NNET), generalized linear model (GLM), and gradient boosting machine (GBM). …”
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High-risk adverse events in two types of single inhaler triple-therapy: a pharmacovigilance study based on the FAERS database by Zhishen Ruan, Chunbin Wang, Shasha Yuan, Yiling Fan, Bo Xu, Xiaodong Cong, Dan Li, Qing Miao

“…We use reporting odds ratio (ROR), proportional reporting ratio (PRR), and Bayesian confidence propagation neural network (BCPNN) for disproportionality analysis. …”
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Using a robust model to detect the association between anthropometric factors and T2DM: machine learning approaches by Nafiseh Hosseini, Hamid Tanzadehpanah, Amin Mansoori, Mostafa Sabzekar, Gordon A. Ferns, Habibollah Esmaily, Majid Ghayour-Mobarhan

“…The performance of the KNN model was compared with Artificial neural network (ANN) and support vector machine (SVM) models. …”
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Forecasting Weather using Deep Learning from the Meteorological Stations Data : A Study of Different Meteorological Stations in Kaski District, Nepal by Supath Dhital, Kapil Lamsal, Sulav Shrestha, Umesh Bhurtyal

“…This project aims to forecast the next 2-hour Precipitation and Air Temperature for Pokhara Domestic Airport meteorological station and the next day's Precipitation, Maximum and Minimum Air Temperature forecast for Lumle, Begnas, and Lamachaur meteorological station, total of four meteorological stations of the Kaski District, Nepal using Long Short-Term Memory (LSTM): a Recurrent Neural Network (RNN) and deploy the outputs through the web portal. …”
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Design a Robust DDoS Attack Detection and Mitigation Scheme in SDN-Edge-IoT by Leveraging Machine Learning by Habtamu Molla Belachew, Mulatu Yirga Beyene, Abinet Bizuayehu Desta, Behaylu Tadele Alemu, Salahadin Seid Musa, Alemu Jorgi Muhammed

“…We evaluated four popular classifiers (K-Nearest Neighbor (K-NN), Random Forest (RF), eXtreme Gradient Boosting (XGBoost), and FeedForward Neural Network (FFNN)) on benchmark datasets CICIDS2017 and Edge-IIoTset, conducting both binary and multi-class classifications. …”
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Age-related differences in eye blink-related neural activity and functional connectivity during driving by Emad Alyan, Stefan Arnau, Stephan Getzmann, Julian Elias Reiser, Melanie Karthaus, Edmund Wascher

“…More specifically, younger participants showed an increase in the clustering coefficient and degrees of the networks, reflecting more robust neural network integration. This pattern of higher connectivity measures in younger participants was also observed in the default mode, control, and limbic networks. …”
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Monitoring changes of forest height in California by Samuel Favrichon, Jake Lee, Yan Yang, Yan Yang, Ricardo Dalagnol, Ricardo Dalagnol, Fabien Wagner, Le Bienfaiteur Sagang, Le Bienfaiteur Sagang, Sassan Saatchi, Sassan Saatchi, Sassan Saatchi

“…Exploring the reliability of machine learning methods for temporal monitoring of forest is still a developing field. We train a deep neural network to predict forest height metrics at 10-m resolution from radar and optical satellite imagery. …”
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Multi-task aquatic toxicity prediction model based on multi-level features fusion by Xin Yang, Jianqiang Sun, Bingyu Jin, Yuer Lu, Jinyan Cheng, Jiaju Jiang, Qi Zhao, Jianwei Shuai

“…Objectives: This article presents ATFPGT-multi, an advanced multi-task deep neural network prediction model for organic toxicity. …”
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IoT based intelligent pest management system for precision agriculture by Salman Ahmed, Safdar Nawaz Khan Marwat, Ghassen Ben Brahim, Waseem Ullah Khan, Shahid Khan, Ala Al-Fuqaha, Slawomir Koziel

“…The size of the dataset is 1000+ images categorized into two groups: (1) fruit fly and (2) not fruit fly and a convolutional neural network (CNN) classifier was trained based on the following features: (1) Haralick features (2) Histogram of oriented gradients (3) Hu moments and (4) Color histogram. …”
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Rapid diagnosis of bacterial vaginosis using machine-learning-assisted surface-enhanced Raman spectroscopy of human vaginal fluids by Xin-Ru Wen, Jia-Wei Tang, Jie Chen, Hui-Min Chen, Muhammad Usman, Quan Yuan, Yu-Rong Tang, Yu-Dong Zhang, Hui-Jin Chen, Liang Wang

“…Multiple ML models were constructed and optimized, with the convolutional neural network (CNN) model achieving the highest prediction accuracy at 99%. …”
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