PSO optimized Feed Forward Neural Network for offline Signature Classification

Popular optimization techniques, as genetic algorithm (GA) and particle swarm optimization (PSO), were used to design the shape of the ground plane in order to improve

In this study, a predictive controller using a feed- forward neural network with online adaptation of the parameters was used in the temperature control of a batch process for

In addition, a novelty of this study is the use of PSO to not only reach the relevant lags used in the prediction, but also to determine the best neural network architecture

A mulit-layer artificial neural network, with a backpropagation training algorithm and 11 neurons in the input layer, was used.. In this type of network, network inputs are

We introduce the features that need to be ranked as inputs of a feed-forward neural network (with a single hidden layer) used as a classifier that distinguishes attacks from

Since artificial neural network (ANN) and particle swarm optimisation (PSO) techniques have never been used in the previously reported work, this work proposes a combination of ANN

Taking into account the real-time optimization of membership functions with the best weights given by trained neural network, the best settling time and rise time values are

In this paper, an RBF neural network was used as a classifier in the face and fingerprint recognition system in which the inputs to the neural network are