MODEL OF CLONAL SELECTION FOR FORECASTING TIME SERIES WITH MISSING DATA

Abstract

This paper proposes the hybrid method of short-term forecasting of time series with missing values using artificial immune systems. A model of the prediction based on the model of clonal selection, which uses heterogeneous antibodies that are based on the case based reasoning method and simple prediction models. The experimental results illustrate the features of the proposed approach.