Predict octane number for gasoline blends

A model with five independent variables is used to predict the octane number of gasoline blends with more accuracy than any previous model. Often, it is useful to know the resulting octane number before the gasoline is blended. Clearly, such a model is useful because good predictive models have been few and far between. With high-powered and faster personal computers, regressional analyses are quite easy to perform with many more independent variables. The objective here was to develop an empirical equation using the regressional analyses are quite easy to perform with many more independent variables. The objective here was to develop an empirical equation using the regression analysis technique to predict the octane rating of 16 blends of motor gasoline. Predicted results for the 16 blends of gasolines were compared with experimental results obtained on CFR engines. Predicted results from the proposed empirical model were in agreement with the experimental data with an average deviational error of 0.54%.