A data mining approach to support the development of new fuels and technology

摘要

In the present work, data mining techniques are used to model the non trivial relationships between properties that characterize the fuels, engine technologies and car emissions. Using models to predict car emissions from fuel properties and technologies engines can improve their development process. To support models of relational data, using the Object Linking and Embedding Database for Data Mining technology, a Simple Naive Bayes Incremental classifier was implemented in Microsoft~R SQL Server~(TM), supporting numeric input attributes, multiple prediction attributes and incremental update of data. Computational experiments using real word data sets were made to evaluate the results obtained by this classifier.