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Abstract. This scientific paper is dedicated to the use of artificial neural networks for the ecological prediction of state of the atmospheric air of an industrial city for capability of the operative environmental decisions. In the paper, there is also the described development of two types of prediction models for determining of the air pollution index on the basis of neural networks: a temporal (short-term forecast of the pollutants content in the air for the nearest days) and a spatial (forecast of atmospheric pollution index in any point of city). The stages of development of the neural network models are briefly overviewed and description of their parameters is also given. The assessment of the adequacy of the prediction models, based on the calculation of the correlation coefficient between the output and reference data, is also provided. Moreover, due to the complexity of perception of the «neural network code» of the offered models by the ordinary users, the software implementations allowing practical usage of neural network models are also offered. It is established that the obtained neural network models provide sufficient reliable forecast, which means that they are an effective tool for analyzing and predicting the behavior of dynamics of the air pollution in an industrial city. Thus, this scientific work successfully develops the urgent matter of forecasting of the atmospheric air pollution index in industrial cities based on the use of neural network models.

Abstract. This paper deals with a specialized Markov chain for a reliability model of the faulttolerant system with dual-type failures, non-synchronized repairs and full restore after reaching the failed state. A generalized iterative procedure for calculation of the system's stationary availability factor, the mean time of repair and the mean time of failure is introduced. An application of the specialized Markov chain in the reliability model of the fault-tolerant duallevel disk arrays 'RAID-10' and calculation of the mean time to data loss by using the generalized iterative procedure are also observed. Finally, calculation examples of mean time to data loss of the RAID-10 array are also given.

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