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3 days ago ， The objective of this work is to propose a novel methodology for improving HEC prediction accuracy. This study uses two original datasets, namely questionnaire ...
5 days ago ， The results show that the developed surrogate models can dramatically reduce computation time (from over 5 hours to less than a second for a single prediction) ...
3 days ago ， Although it is feasible to apply trained predictive models to multiple building types using transfer learning technique, their expandability is still limited.
4 days ago ， In this study, we investigate how the properties of water penetration, chlorine resistance, and compressive strength can be predicted by polynomial regression ...
4 days ago ， This study presents an interpretable traffic flow forecasting framework based on popular tree-ensemble algorithms.
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7 days ago ， The paper covers fundamental concepts such as descriptives and outliers, smoothing, amplitude and phase variation, and functional principal component analysis.
4 days ago ， This paper presents FORSEER (Forecasting by Selective Ensemble Estimation and Reconstruction), a novel methodology designed to address temperature forecast.
2 days ago ， Machine learning algorithms, particularly polynomial regression, excel in capturing complex and non-linear relationships in data due to their ability to model ...
4 days ago ， PDF | This paper studies the forecasting power of uncertainty emanating from the commodities market, energy market, economic policy, and geopolitical.
22 hours ago ， This study investigates wind speed prediction using advanced machine learning techniques ... Building thermal load prediction through shallow machine learning ...