ANN Tools for Number Series

Any mathematical pattern can be the generation principle for number series. In con-
trast to most of the application fields of artificial neural networks (ANN) a successful
solution does not only require an approximation of the underlying function but to correctly
predict the exact next number. We propose a dynamic learning approach and evaluate our
method empirically on number series from the Online Encyclopedia of Integer Sequences.
Finally, we investigate research questions about the performance of ANNs, structural prop-
erties, and the adequate architecture of the ANN to deal successfully with number series.
Solving number series poses a challenging problem for humans and Artificial Intelligence
Systems. The task is to correctly predict the next number in a given series, in accordance
with a pattern inherent to that series. We propose a novel method based on Artificial
Neural Networks with a dynamic learning approach to solve number series problems. Our
method is evaluated on an own experiment and over 50.000 number series from the Online
Encyclopedia of Integer Sequences (OEIS) database.

Leave a Reply

Your email address will not be published. Required fields are marked *