Developing and training model of artificial neural network for creating decision support systems

The article highlights the significant increase of industrial capacities and automation of production, which requires taking effective management decisions by a responsible person. There have been outlined the important achievements of the scientists in application of the artificial neural networks in the various fields of activity and decision support systems involving the information analysis and processing with the results obtained. There has been proposed a review of publications on training artificial neural networks and on their efficient application in solving problems of classification, prediction and control. The most common structures of neural networks, their advantages and disadvantages, as well as the methods used to create training data arrays have been studied. A comparative analysis of using various structures of artificial neural networks and the effectiveness of existing teaching methods and the prospects for their use has been carried out. There has been defined the most preferred neural network topology for solving problems of fire safety management at the production facilities as an active decision support system. Using the analysis results, the most common and effective training methods have been identified, application of which is appropriate for developing and training various types of neural networks. The use of the technology is well grounded for reducing the errors in data processing, the financial costs for ensuring security, as well as for possible using the neural networks in the decision support systems to optimize these systems.