Solar radiation forecasting with multiple parameters neural networks YashwantKashyap, ...Anil K.Sao, inRenewable and Sustainable Energy Reviews, 2015 2.1Feedforward Network (FFN) Consequently, weighted information relocates a layer to a new level; this is the reason it is calledfeedforward. FFN, ...
In this way, we present a Salp Swarm Optimization based Feedforward Neural Network (SSO-FFN) to build an intrusion detection methodology for computer networks. The performance of SSO-FFN over the state-of-the-art intrusion detection methodologies was validated using NSL-KDD cup intrusion dataset ...
Another special case of the proposed error function can be used for training class-balancing neural networks (CBNNs), which are developed to handle class imbalance by relying on class-specific correction (CSC). VCNNs and CBNNs are compared with conventional feedforward neural networks (FFNNs), ...
In this paper, an integration between the particle swarm optimization (PSO) algorithm and feedforward neural networks (FFN) for the indicator the damaged elements in structure of a steel 2D frame structure. The FNN optimization includes the optimization of weights and bias. And usually, the gradie...
Previous researches mostly adopt pure feedforward networks (FFNs) to study how the network structure affects spiking regularity propagation, which ignore the role of local dynamics within the layer. In this paper, we construct an FFN with recurrent connections and investigate the propagation of ...
Feedforward networkFitzHugh-Nagumo neuronDegree distributionSignal propagationCoherence resonanceWe focus on the effects of degree distributions on signal propagation in noisy feedforward networks (FFNs) based on the FitzHugh-Nagumo neuron model. Three FFN topologies are constructed with the same number of...
Previous researches mostly adopt pure feedforward networks (FFNs) to study how the network structure affects spiking regularity propagation, which ignore the role of local dynamics within the layer. In this paper, we construct an FFN with recurrent connections and investigate the propagation of ...
Feedforward networkFitzHugh-Nagumo neuronDegree distributionSignal propagationCoherence resonanceWe focus on the effects of degree distributions on signal propagation in noisy feedforward networks (FFNs) based on the FitzHugh鈥揘agumo neuron model. Three FFN topologies are constructed with the same number ...
and the resonance performance is studied at the neuronal level, where it is found that both the average membrane potentials and the Q indexes of neurons in FFN with identical degree distribution is more consistent with each other than that of the other two FFNs due to their network topologies....
neural codesynaptic delayWe focus on the role of heterogeneity on the propagation of firing patterns in feedforward network (FFN). Effects of heterogeneities both in parameters of neuronal excitability and synaptic delays are investigated systematically. Neuronal...