Paper
12 April 2004 A new data mining tool for analyzing coumarin-based prodrugs
Hao Fang, Jun Li, Yi Sun, Binghe Wang, Yan-Qing Zhang
Author Affiliations +
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.
© (2004) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Hao Fang, Jun Li, Yi Sun, Binghe Wang, and Yan-Qing Zhang "A new data mining tool for analyzing coumarin-based prodrugs", Proc. SPIE 5433, Data Mining and Knowledge Discovery: Theory, Tools, and Technology VI, (12 April 2004); https://doi.org/10.1117/12.541595
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KEYWORDS
Chemical analysis

Data mining

Neural networks

Data processing

Error analysis

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