Predicting the parameters of energy installations with laser ignition: neural network models

The article considers the possibility of using artificial neural networks for prediction of the parameters of the model energy installation with laser ignition. The main stages of creating a prognostic model based on artificial neural network have been presented. Input data were analyzed by principal component method. The synthesized neural network was built up to predict the parameter value of the model in question. The artificial neural network was trained by back-propagation algorithm. The efficiency of the artificial neural networks and their applicability to prediction of the parameter values of the various elements of rocket engines were demonstrated.