Amended Fruit Fly Algorithm

This research presents the optimization of radial basis function (RBF) neural network using aFOA and establishment of the network model adopting it with the combination of the evaluation of the mean impact value (MIV) to select variables. The form of amended fruit fly optimization algorithm (aFOA) is easy to learn and has the characteristics of quick convergence and not readily dropping into local optimum. The validity of the model is tested by two actual examples furthermore it is simpler to learn more stable and practical.