Development of a Mobile System for Interactive Forecasting of Statistical Graph Data

The paper describes a mobile software system that recognizes function graphs using computer vision and machine learning methods, their analysis and prediction using several intelligent algorithms. The used approaches to the recognition of graphs, algorithms for forecasting time series and the architecture of the software system are described. The developed approaches can be used in various fields, including in the formation of patient-oriented recommendations as a result of the analysis of graphical diagnostic data. In conclusion, the results of experiments on the operation of the system are given on the example of recognition and analysis of several graphs of functions.