Application of Genetic Neural Network to Decision Support System for Environmental Control and Life Support System

The environmental control and life support system (ECLSS) of manned spacecraft consumes long training period for learning model due to huge number of ECLSS parameters and uncertain factors,so that it is hard to predict those parameters quickly and accurately in real time. This paper presents a new ECLSS parameters prediction model based on a genetic neural network by optimizing BP neural network with a genetic algorithm,and develops a simulation software. The model is verified by real spacecraft flying data in the case of predicting obit cabin pressure. It is proved that the training epochs of the genetic neural network are 30% less than that of BP network within the same error limitation,and the former has smaller mean error. So it is believed that the genetic neural network based model can predict the key parameters more accurately and fast for ECLSS decision support system.