Addition-Subtraction Frequency (ASF) Algorithm Based Prediction of Important Sequence 2 via 3 Inputs, 5 Inputs and 7 Inputs with Full Traversal

摘要

This paper makes an attempt to predict future years of important sequence 2 (i.e., U.S. president non-electoral, USPNE). The ASF algorithm, which has been used for many prediction tasks, is employed to make the prediction. Concretely, historical data of USPNE are taken as the input data, and, for further validation and consistency, 3-input ASF algorithm, 5-input ASF algorithm and 7-input ASF algorithm using full traversal are applied in numerical experiments, respectively and comparatively. After consistency analysis, years 2025, 2027, 2036, 2045, 2047, 2056 and 2067 are of relatively high possibility to be future years of such an important sequence 2, especially, 2025.