Interpretation and Forecasting Processes, Represented by Time Series, on the Basis of the Extended Logistic Mapping

The article studies a possibility of use of methods of non-linear dynamics for structuring an operative forecast of complex and structured processes described by time series. It offers a model of extended logistic mapping for interpretation of characteristics of dynamic processes. It studies procedures of interpretation of data and forecasting parameters of the processes, represented by time series, that use models of extended logistic mapping. It offers methods of recurrent structuring of an operative forecast. In order to increase accuracy of obtained results, the article recommends to correct values of model parameters by means of assessment of new sets of values by the method of exponential smoothing. It provides results of application of the model of extended logistic mapping for structuring an operative forecast of processes of the railway transport, in particular, assessment of parameters of the carriage traffic volumes.