A neural network based-approach for structural health monitoring was presented. The proposed approach involves two steps. The first step, system identification, uses NARX (Non-linear Auto-Regressive with eXogenous) neural networks to identify the undamaged and damaged states of a structural system. The second step, structural damage detection, uses the aforementioned trained NARX neural network...

The aim of the study is to find right architecture NARX neural network, in order perform daily prediction maximum wind speed Laayoune city. We relied on Levenberg-Marquardt optimization algorithm. RMSE error metric showed that NARX-SP outperforms NARX-P.

The complexity of helicopter flight dynamics makes modeling and helicopter system identification a very difficult task. Most of the traditional techniques require a model structure to be defined a priori and in case of helicopter dynamics, this is difficult due to its complexity and the interplay between various subsystems. To overcome this difficulty, non-parametric approaches are commonly ado...

Recurrent neural networks (RNNs) have shown success for many sequence-modeling tasks, but learning long-term dependencies from data remains difficult. This is often attributed to the vanishing gradient problem, which shows that gradient components relating a loss at time t to time t− τ tend to decay exponentially with τ . Long short-term memory (LSTM) and gated recurrent units (GRUs), the most ...

-One o f the issues in any learning model is how it scales with problem size. The problem o f learning finite state machine (FSMs) from examples with recurrent neural networks has been extensively explored. However, these results are somewhat disappointing in the sense that the machines that can be learned are too small to be competitive with existing grammatical inference algorithms. We show t...

Abstract The electronic skin described in the article comprises screen-printed graphene-based sensors, intended to be used for robotic applications. precise mathematical model allowing touch pressure estimation is required during its calibration. describes recurrent neural network calibration, which parameters are not homogeneous, and force characteristics have visible hysteretic behaviour. pre...

Freshwater supply is a major challenge in regions with limited water resources and extremely arid climatic conditions. The objective of this study to model the monthly demand Kuwait using nonlinear autoregressive exogenous input (NARX) neural network approach. country lacks conventional surface characterized by climate. In addition, it has one fastest growing populations. study, linear detrendi...