Neural networks feedforward back-propagation

Feedforward Back-propagation Neural Network %Network structure l 10(tansig) l(purelin)... 

Jouyban et al. (2004) applied ANN to calculate the solubility of drugs in water-cosolvent mixtures, using 35 experimental datasets. The networks employed were feedforward back-propagation errors with one hidden layer. The topology of neural network was optimized in a 6-5-1 architecture. All data points in each set were used to train the ANN and the solubilities were back-calculated employing the trained networks. The difference between calculated solubilities and experimental... 

As is shown in Figure 1, BP neural network is a multi-layer feedforward network with error back-propagation learning, which consists of an input layer, an output layer and several hidden layers. Each layer includes a set of neurons interconnected by weight (Han et al. 2009). 

Another multilayer network type is the multilayer feedforward network (see Neural Networks in Chemistry) that is usually trained by the back-propagation algorithm (Figure 2). The architecture of such a network can be quite variable, depending on the number of input units, the number of neurons, and the number of output neurons. In the case of training... 

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