An Unified View on the Feedforward Neural Network ArchitectureUnified viewFeedforward Neural NetworksEnsemble learningSwarm intelligenceParticle swarm optimizationIn this paper, an unified view on feedforward neural networks (FNNs) is provided from the free perception of the architecture design, learning ...
This dissertation investigated the predictability of five currency exchange rates by comparing a nonlinear approach based on the feedforward neural network model to three traditional linear models. The predictability comparison results generally favor the neural network model, in that a neural network ...
Feedforward neural networks for the identification of dynamic process. Thibault J. Chemical Engineering Communications . 1991Thibault, J. , “ Feedforward Neural Networks for the Identification of Dynamic Processes ”, Chem. Eng. Commun. 105 , 109 – 128 ( 1991 )....
In this paper, we propose a genetic algorithm based design procedure for a multi-layer feed-forward neural network. A hierarchical genetic algorithm is use... G Yen,H Lu - 《International Journal of Neural Systems》 被引量: 34发表: 2008年 Simulation of biodegradation process in a fluidized ...
The structure of the feedforward neural network (FNN) was 18 inputs (four for glottal and 14 for speech samples), 3 neurons in the hidden layer and one output. The results have shown that, after pruning, the glottal signal has no effect on the model for a female speaker, while it ...
One feedforward neural network, known as the multilayer perceptron (MLP), performs the same task as LDA and logistic regression which, a priori, makes it appropriate for the treatment of financial information. In this paper, a practical case based on data from Spanish companies...
2.2 Feedforward neural networks: the perceptrons A neural network is made up of layers of information processing units called neurons. Each neuron performs a simple weighted sum of the information it receives. The weightings or coefficients are called synaptic weights in neural network jargon. A tr...
【Deep Learning】笔记:Understanding the difficulty of training deep feedforward neural networks,程序员大本营,技术文章内容聚合第一站。
Entropy error functionConvergenceMonotonicityGradient method is often used for the feedforward neural network training. Most of the studies so far have been focused on the square error function. In this paper, a novel entropy error function is proposed for the feedforward neural network training. ...
The most widely used kind of neural network today has a multi-layer perceptron (MLP) structure, and because of how significant signal release and network behavior similar to that of the human brain are in these networks, they are sometimes referred to as the Feedforward networks (Jahed Arm...