This paper is an attempt to assess the potential and usefulness of ANN based modeling for evaporation prediction from a reservoir, where in classical and empirical equations failed to predict the evaporation accurately. The meteorological data set of daily pan evaporation, temperature, solar radiation, relative humidity, wind speed is used in this study. The performance of feed forward back pro...

BACKGROUND Feed-forward motifs are important functional modules in biological and other complex networks. The functionality of feed-forward motifs and other network motifs is largely dictated by the connectivity of the individual network components. While studies on the dynamics of motifs and networks are usually devoted to the temporal or spatial description of processes, this study focuses on...

In this paper a nonparametric neural network (NN) technique for prediction of future values of a signal based on its past history is presented. This approach bypasses modeling, identification, and parameter estimation phases that are required by conventional parametric techniques. A multi-layer feed forward NN is employed. It develops an internal model of the signal through a training operation...

Introduction Sound vibrations are collected from the external environment by the eardrum and are guided to the basilar membrane in the cochlea. Pressure differences in the two scalae of the cochlea result in a traveling wave on the basilar membrane (figure 1). The tiny displacements are detected by the deflection of thousands of hair cells, situated along this membrane. It is hypothesized that ...

Basic definitions concerning the multi-layer feed-forward neural networks are given. The back-propagation training algorithm is explained. Partial derivatives of the objective function with respect to the weight and threshold coefficients are derived. These derivatives are valuable for an adaptation process of the considered neural network. Training and generalisation of multi-layer feed-forwar...

Network motifs play an important role in the qualitative analysis and quantitative characterization of networks. The feed-forward loop is a semantically important and statistically highly significant motif. In this paper, we extend the definition of the feed-forward loop to subgraphs of arbitrary size. To avoid the complexity of path enumeration, we define generalized feed-forward loops as pair...