Paradigm predictive analysis of two-phase Eyring–Powell fluid flow over a vertical stretching sheet with temperature-dependent viscosity by multilayer neural networks by Zahoor Shah, Hamza Iqbal, Waqar Azeem Khan, Taseer Muhammad, Muhammad Shoaib

“…The novel DLNNs-LMA were used for the numerical computations on the reference data. The error analysis indicates a close correlation with the proposed databases and with reference datasets, having values between 10-3 and 10-9, which indicates a high accuracy of the proposed methodology. …”
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Optical OTFS waveform PAPR analysis for high order modulation employing CNN, DNN, and AE machine learning algorithms under a variety of channel scenarios by Arun Kumar, Nishant Gaur, Aziz Nanthaamornphong

“…Moreover, Bit Error Rate (BER) performance tests demonstrate an SNR improvement of 8.2 dB and 3.9 at a BER of 10-5, guaranteeing error-free data transmission for diverse mobility scenarios. …”
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Quinary Classification of Human Gait Phases Using Machine Learning: Investigating the Potential of Different Training Methods and Scaling Techniques by Amal Mekni, Jyotindra Narayan, Hassène Gritli

“…The first approach adopts stratified random sampling, where 80% of the data from each subphase are allocated for training and 20% for testing. …”
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Application of Partial Least Squares-Discriminate Analysis Model Based on Water Chemical Compositions in Identifying Water Inrush Sources from Multiple Aquifers in Mines by Yaoshan Bi, Jiwen Wu, Xiaorong Zhai, Shuhao Shen, Libin Tang, Kai Huang, Dawei Zhang

“…To improve model accuracy and predictive ability, hierarchical clustering analysis method was used to eliminate seven unqualified water samples to reduce the errors caused by improper data. …”
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Understanding the efficiency and uncertainty of water supply service assessment based on the Budyko framework: A case study of the Yellow River Basin, China by Tingjing Zhang, Quanqin Shao, Haibo Huang

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Facility-Based Delivery during the Ebola Virus Disease Epidemic in Rural Liberia: Analysis from a Cross-Sectional, Population-Based Household Survey. by John Ly, Vidiya Sathananthan, Thomas Griffiths, Zahir Kanjee, Avi Kenny, Nicholas Gordon, Gaurab Basu, Dale Battistoli, Lorenzo Dorr, Breeanna Lorenzen, Dana R Thomson, Ami Waters, Uriah G Moore, Ruth Roberts, Wilmot L Smith, Mark J Siedner, John D Kraemer

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Bayesian Neural Networks With Robust Feature Interpretation for Enhanced Compressive Strength Prediction of Ultra‐High‐Performance Concrete by Tao Zhang, Ji Hao, Jie Zhang, Lina Du, Yunhao Zhang, Wenbin Jiao

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Automatic Threshold Selection for Generalized Pareto and Pareto–Poisson Distributions in Rainfall Analysis: A Case Study Using the NOAA NCDC Daily Rainfall Database by Roberto Mínguez

“…This study develops an automatic, statistically sound procedure for optimal threshold selection, leveraging weighted mean square errors and internally studentized residuals. The proposed method outperforms existing approaches in terms of accuracy, as demonstrated through numerical experiments and its application to real-world data from the NOAA NCDC Daily Rainfall Database. …”
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Three-Dimensional Analysis of Seepage in Fractured Rock Masses and Evaluation of the Accuracy of Empirical Methods for Predicting Permeability in Cutoff Walls: A Case Study of Cham... by Alireza Baghbanan, Masoud Dararbi, Amirhosein Momeni, Ahmad Rahmani Shahraki, Amin Azhari

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Mapping EQ-5D-5L Score From SGRQ in Patients with Asthma and/or COPD in NOVELTY by Jackson D, Quinton A, Zhang F, Müllerová H, Janson C, Sadatsafavi M

“…Performance (mean square errors [MSE]) was evaluated relative to the Starkie et al algorithm in the validation sample (Year 2 and Year 3 data).Results: A total of 6813 patients (asthma: 3546; asthma+COPD: 872; COPD: 2395) with available EQ-5D-5L and SGRQ data were included at baseline. …”
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Solar Flare Prediction Using Long Short-term Memory (LSTM) and Decomposition-LSTM with Sliding Window Pattern Recognition by Zeinab Hassani, Davud Mohammadpur, Hossein Safari

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3D modelling and x-ray depth analysis map of the pulp with computer software via digital periapical radiography and cone beam computed tomography by Turgut Felek, Samed Satir, Selale Ozel, H. Kursat Celik

“…The aim of this study was to create a software (XPAR) which obtains x-ray depth analysis and 3D modelling of the pulps of single-rooted teeth by converting the grey values in the original radiographs into numerical data. …”
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Approaches to Proxy Modeling of Gas Reservoirs by Alexander Perepelkin, Anar Sharifov, Daniil Titov, Zakhar Shandrygolov, Denis Derkach, Shamil Islamov

“…The methodology integrates graph neural networks to account for spatial interdependencies between wells with recurrent and convolutional neural networks for time-series analysis. The model was validated using an extensive set of hydrodynamic simulation calculations and real-world field data. …”
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Research on Forecasting Sales of Pure Electric Vehicles in China Based on the Seasonal Autoregressive Integrated Moving Average–Gray Relational Analysis–Support Vector Regression M... by Ru Yu, Xiaoli Wang, Xiaojun Xu, Zhiwen Zhang

“…Finally, a combined model incorporating different algorithms was verified against market sales data to explore the optimal sales prediction approach. …”
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The Alphabetical Book of Red Army Conscripts by Military Commissariat of Ulan-Kholsky District: Analyzing Mobilization Arrangements in the Kalmyk ASSR by Valentina N. Ochir-Goryaeva

“…The conducted analysis has revealed quite a variety of repetitions, errors, and inaccuracies. …”
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Heightened demand for mental health information resources during the SARS-CoV-2 pandemic in Germany: A retrospective longitudinal analysis of helpline calls by Jil Zippelius, Simon Schreynemackers, Ulrich Hegerl, Hanna Reich

“…This study investigated the impact of the SARS-CoV-2 pandemic on hotline usage trends through a time-series analysis. Methods: Based on longitudinal data from 2018 to 2022 predictive models were developed for caller trends on the Info-Telefon Depression. …”
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An Intelligent Method for Day-Ahead Regional Load Demand Forecasting via Machine-Learning Analysis of Energy Consumption Patterns Across Daily, Weekly, and Annual Scales by Monica Borunda, Arturo Ortega Vega, Raul Garduno, Luis Conde, Manuel Adam Medina, Jeannete Ramírez Aparicio, Lorena Magallón Cacho, O. A. Jaramillo

“…A case study using hourly load demand time-series data provided by the Centro Nacional de Control de Energía (CENACE) is analyzed, and the mean absolute percentage error (MAPE) is calculated, showing lower MAPE than traditional methods. …”
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Trend and prediction of daily incidence of hand, foot, and mouth disease in Shenzhen, 2011 - 2023 with projections to 2024: a Prophet model approach by Wenhai LU, Lixia SONG, Huawei XIONG, Zhigao CHEN, Yan LU, Yanpeng CHENG, Zhen ZHANG

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Numerical Background-Oriented Schlieren for Phase Reconstruction and Its Potential Applications by Shiwei Liu, Yichong Ren, Haiping Mei, Zhiwei Tao, Shuran Ye, Xiaoxuan Ma, Ruizhong Rao

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Dynamic Accident Network Model for Predicting Marine Accidents in Narrow Waterways Under Variable Conditions: A Case Study of the Istanbul Strait by Serdar Yıldız, Özkan Uğurlu, Xinjian Wang, Sean Loughney, Jin Wang

“…Accident analysis models are crucial tools for understanding and preventing accidents in the maritime industry. …”
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