Knowledge Reduction of Evaluation Dataset Based on Genetic Algorithm and Fuzzy Rough Set

In order to obtain better attribute reduction of the continuous dataset, genetic algorithm and fuzzy rough set were used. By making use of this method, the discretization process of continuous attributes was avoided, and the information loss was reduced, the reduction was quickened, the decision dependency was raised in comparison with the traditional rough set. Here a simulation example was used to test the efficiency of this method firstly. Then it was applied to the reduction of evaluation dataset about satellite navigation system combat effectiveness. The simulation result has shown that it can obtain those input features that are most predictive of a given outcome and realize the dataset preprocess, which is helpful to realize the combat effectiveness evaluation.