A novel approach for noise prediction using Neural network trained with an efficient optimization technique

A novel approach for noise prediction using Neural network trained with an efficient optimization technique

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Aerofoil noise as self-noise is detrimental to system performance, in this paper NACA 0012 optimization parameters are presented for reduction in noise.Designing an aerofoil with little noise is a fundamental objective of designing an aircraft that physically and functionally meets the requirements.Aerofoil self-noise is the noise created by aerofoils interacting with pioneer ddj sz dimensions their boundary layers.Using neural networks, the suggested method predicts interlock ettore aerofoil self-noise.For parameter optimization, the quasi-Newtonian method is utilised.

The input variables, such as angle of attack and chord length, are used as training parameters for neural networks.The output of a neural network is the sound pressure level, and the Quasi Newton method further optimises these parameters.When compared to the results of regression analysis, the values produced after training a neural network are enhanced.