in this paper, the artificial neural network (ann) approach is applied for forecasting groundwater level fluctuation in aghili plain,southwest iran. an optimal design is completed for the two hidden layers with four different algorithms: gradient descent withmomentum (gdm), levenberg marquardt (lm), resilient back propagation (rp), and scaled conjugate gradient (scg). rain,evaporation, relative...

The present design of echo state network (ESN) parameters relies on the selection of the maximum eigenvalue of the linearized system around zero. However, this has been found far from optimal for function approximation. This letter presents a function approximation perspective to better understand the operation of ESNs and proposes an information-theoretic measure, the average entropy of echo s...

Echo State Networks (ESN) are reservoir networks that satisfy well-established criteria for stability when constructed as feedforward networks. Recent evidence suggests that stability criteria are altered in the presence of reservoir substructures, such as clusters. Understanding how the reservoir architecture affects stability is thus important for the appropriate design of any ESN. To quantit...

Enterprise social networking (ESN) techniques have been widely adopted by firms to provide a platform for public communication among employees. This study investigates how the relationships between stressors (i.e., challenge and hindrance stressors) and employee innovation are moderated by task-oriented and relationship-oriented ESN use. Since challenge-hindrance stressors and employee innovati...

With more companies using Enterprise Social Networks (ESN) for employee communication and collaboration, the influence of ESN on organizational hierarchies has been subject of discussions in science and practice. Conversely, the question if formal hierarchies affect interaction inside ESN and outside (i.e., personal interaction or interaction via traditional media) in the same way has not yet b...

HIV-specific T cells response and T cell activation are frequently seen in exposed seronegative individuals (ESN). In this study, we report HIV-specific response and level of T cell activation in ESN partners of HIV-infected patients presenting low or undetectable levels of HIV-RNA. We evaluated 24 HIV-serodiscordant couples. ESN were classified into three categories of exposure to HIV (very lo...

Recurrent neural networks (RNNs) are useful tools for learning nonlinear relationships in time series data with complex temporal dependences. In this paper, we explore the ability of a simplified type of RNN, one with limited modifications to the internal weights called an echostate network (ESN), to effectively and continuously decode monkey reaches during a standard center-out reach task usin...

Reservoir computing (RC) is a novel approach to time series prediction using recurrent neural networks. In RC, an input signal perturbs the intrinsic dynamics of a medium called a reservoir. A readout layer is then trained to reconstruct a target output from the reservoir’s state. The multitude of RC architectures and evaluation metrics poses a challenge to both practitioners and theorists who ...