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Figure A1. Simple neural network. ReLU: rectified linear unit.

Figure A1. Simple neural network. ReLU: rectified linear unit.

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Figure 1. (a) Schematic concept of data augmentation by newly produced...
Figure 2. Architecture and corresponding dataset of the artificial...
Figure 3. Comparison of mean absolute percentage error (MAPE) for...
Figure 4. Prediction accuracy of MO and MA,760 models for the test...
+2 Figure A1. Simple neural network. ReLU: rectified linear unit.
Predicting Pressure Sensitivity to Luminophore Content and Paint Thickness of Pressure-Sensitive Paint Using Artificial Neural Network
Article
Full-text available
  • Jul 2021
An artificial neural network (ANN) was constructed and trained for predicting pressure sensitivity using an experimental dataset consisting of luminophore content and paint thickness as chemical and physical inputs. A data augmentation technique was used to increase the number of data points based on the limited experimental observations. The predi...
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Figure 1. Simple neural network.
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Pressure Sensitivity Prediction for Pressure-Sensitive Paint Development using Artificial Neural Network
Conference Paper
Full-text available
  • Jan 2022
View Video Presentation: https://doi.org/10.2514/6.2022-1662.vid The present study investigates the applicability of the artificial neural network (ANN) model to predict the pressure sensitivity to chemical and physical factors. The ANN model was constructed and trained using an experimental and augmented dataset consisting of paint thickness, lumi...
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