Prediction on Vibro-Wind Energy Harvester

The Vibro-wind energy harvester designed in various geometric shapes and sizes. The ultimate aim is to collect the samples from various design and to avoid designing harvester for analysis in the future, the prediction model has been applied on collected samples. The data has been collected as physical properties of a harvester, oscillation frequency, and vibration parameters. Based on the physical properties the neural network back-propagation model predicted the vibration parameters and frequency. The model has been evaluated with Mean Square error Value (MSE) and Mean Absolute error value which are found as 0.005826 and 0.07 respectively.