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An Advanced Approach for Predicting Workpiece Surface Roughness Using Finite Element Method and Image Processing Techniques
Published 2024-11-01“…By employing range and regression analyses methods, this study quantitatively evaluates the interdependencies among cutting parameters, forces, temperatures, and roughness, subsequently formulating a multivariate regression model to predict surface roughness. Finally, a turning experiment under actual working conditions was conducted, confirming the model’s capacity to predict the <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><msub><mrow><mi>R</mi></mrow><mrow><mi>a</mi></mrow></msub></mrow></semantics></math></inline-formula> trend with an accuracy of 85.07%. …”
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Prediction method of TBM excavation axis deviation for small turning tunnels based on LSTM neural network
Published 2024-12-01Get full text
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Investigation of ML algorithms for prediction of CFD data of fluid flow inside a packed-bed reactor
Published 2025-06-01Get full text
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FATIGUE LIFE PREDICTION OF NOTCHED STRUCTURE USING COMBINED CRITICAL PLANE-CRITICAL DISTANCE APPROACH (MT)
Published 2023-01-01Get full text
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Forecasting the Timing of Peak Solar Flare Index in Solar Cycle 25 for Improved Space Weather Prediction
Published 2025-01-01Get full text
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Advancing the Prediction and Evaluation of Blast-Induced Ground Vibration Using Deep Ensemble Learning with Uncertainty Assessment
Published 2025-05-01“…This study aims to propose a deep ensemble model to predict the blast-induced ground vibration and quantify the prediction uncertainty, which is usually not addressed. …”
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Deep Learning Framework for Predicting Transonic Wing Buffet Loads Due to Structural Eigenmode-Based Deformations
Published 2025-05-01“…Comparing the pressure loads modeled by the hybrid ROM and the reference full-order numerical solution, an overall good prediction performance is indicated with mean squared error (MSE) values mostly below <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>3</mn><mo>%</mo></mrow></semantics></math></inline-formula>, reaching local maxima of about <inline-formula><math xmlns="http://www.w3.org/1998/Math/MathML" display="inline"><semantics><mrow><mn>12</mn><mo>%</mo></mrow></semantics></math></inline-formula>, due to strong pressure gradients associated with pronounced shock oscillations.…”
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A Dual-View Approach for Multistation Short-Term Passenger Flow Prediction in Bus Transit Systems
Published 2023-01-01Get full text
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