Neural Network-Based Interpolation and Extrapolation of Wind Tunnel Test Data

Abstract

There is an increasing need to apply emerging technologies in knowledge-based management system. This proposed system captures the knowledge of experts and the knowledge acquired for designing a new systems. Wind Tunnel Test data of missiles has been taken into consideration for knowledge management. Interpolation and Extrapolation of missile test data has been attempted using neural network technique General Regression Neural Networks training algorithm. The results produced by neural network training methodologies are validated with the existing test data. The knowledge extraction using neural network is found suitable for interpolation and to some extent for extrapolation, thereby reducing the cost as well as number of test runs in Wind Tunnel Test.

Performance Comparison of Kriging and SVR Surrogate Models Applied to the Objective Function Prediction Within Aerodynamic Shape Optimization

“…(I) parameter controls the error margin permitted for the model, as can be seen in equations (9) and (10). (II) parameter controls the number of outliers allowed on the optimization of the equation (3).…”

“…NN has been used for solving difficult modeling problems [10][11]. NN generally minimizes the sum of the approximation errors at sampling locations, so that the accuracy of the approximated value at a sampling location is relatively high.…”