A new data mining tool for analyzing coumarin-based prodrugs

Hao Fang, Jun Li, Yi Sun, Binghe Wang, Yan-Qing Zhang

Abstract: This paper focuses on using fuzzy neural network data mining techniques to analyze nonlinear relations among chemical factors. Through standardizing and rescaling the raw data, we processed the data into fuzzy neural network not only to learn chemical knowledge from large amounts of experimental data, but also predict future chemical parameters for further experimental verification. The results show that the most relative chemical factor can be obtained by analyzing the experimental errors using fuzzy rules.