Prediction Using Recurrent Neural Network Based Fuzzy Inference system by the Modified Bees Algorithm
In this paper, Recurrent Neural network based fuzzy Inference System (RNFIS) for prediction is proposed. A recurrent network is embedded in the RNFIS by adding feedback connections in the second layer and in the output layer. In this paper, a hybrid learning algorithm is used to train the RNFIS model. This algorithm uses a modified version of the bee's algorithm and Gradient Descent (GD). In the basic version of bees' algorithm, the algorithm performs a kind of neighborhood search combined with random search. To improve the local search ability of the bees' algorithm and help the algorithm to jump out from the local optimum, a modification is performed by applying three kinds of crossovers to the elite individuals based on different conditions of current state.