hierarchical branched system

Програмний комплекс для прогнозування основних характеристик надійності симетричних ієрархічних систем за допомогою штучних нейронних мереж

A software module for the calculation of the basic characteristics of reliability the symmetric hierarchical distributed systems with a deprecated outgoing elements with branching till the level 1. The prediction of reliability characteristics is done using the artificial neural network of the non iterative radial type. The reduced to the mean value range errors of the ANN learning and forecasting are calculated as well as the time estimations for the ANN learning and forecasting.

Prediction of the proper operation and failure probabilities if the completeness of the system is specified for the hierarchical branched till the 4-th level systems using the artificial neural networks

The software module is developed. By the specified readiness parameters it calculates probabilities of the proper operation and failure-ability for the isotropic symmetric and hierarchical branched systems (HBS).The module is tested/restricted against the systems of the n-level branching whose elements obey the exponential rules. The non-iterative artificial neural network (ANN) has been deployed to the prediction of those characteristics.