A new supervised learning algorithm inspired on chemical organic compounds

In this work, a new supervised learning method called artificial organic networks is proposed for modeling problems, i.e. fitting, analyzing, inference and classification. In fact, this technique is inspired on chemical organic compounds due to their characteristics of stability, encapsulation, inheritance, organization, and robustness. Additionally, this work presents artificial hydrocarbon networks, a supervised learning algorithm inspired on chemical hydrocarbon compounds and proposed under artificial organic networks technique. Theoretical and experimental results showed that both artificial organic networks technique and artificial hydrocarbon networks algorithm can be used for fitting functions, modeling systems, and inference and classification purposes. --Abstract p. ii