The radial basis kernel
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Kernel regression models developed with Visual C# .NET for data analysis in construction engineering
This research work relies on kernel regression methods for constructing nonlinear regression models. These models can be used to solve function approximation tasks in construction engineering. The newly developed software program was developed with the Visual C# .NET. The program has been tested with the task of estimating the punching shear strength of steel fibre reinforced concrete slab.
7p nhanchienthien 25-07-2023 6 4 Download
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The SVM model delivered optimum performance with the radial basis kernel, C=10, and gamma=0.0001. In the proposed method, same priority was given to processing time (testing time) and accuracy, as traffic sign identification is time critical. The final accuracy obtained was 87% (with confidence interval 84%-90%) with a processing time of 0.64s (with confidence interval of 0.57s-0.67s) for correct detection at testing, which emphasizes the effectiveness of the proposed method.
5p spiritedaway36 28-11-2021 10 1 Download
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The present study introduces a set of machine learning-based models to predict the heating and cooling loads in buildings. This includes back-propagation artificial neural network, generalized regression neural network, radial basis neural network, radial kernel support vector machines and ANOVA kernel support vector machines.
6p tohitohi 22-05-2020 20 1 Download