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An approach to prediction of the arrival time of interplanetary shocks using neural networks based on the data gathered from single EPAM (Electron, Proton and Alpha Monitor) channel of NASA’s ACE (Advanced Composition Explorer) spacecraft is proposed in this paper. A short description of ACE spacecraft and the data, published online on the appropriate web-site, are considered. A data choice to fulfill a prediction of interplanetary shocks is proven and structure of neural network is described. The results of simulation modeling in MATLAB are considered in the end of the paper.

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The paper considers climatic and weather specifics of the Arctic, identifying dangerous weather factors with the highest frequency. Specificity of flying in the Arctic and state-ofthe-art in flight meteorology are considered. The authors define the tentative approaches to solving tasks in improving quality of flight meteorology in the Arctic using numerical hydrodynamic prognostic methods.

No abstract