Neural network Controller methodology is a nonlinear control fashion equipped with a novel method of Neural Predictive Controller (NPC) as an intelligent optimizer that in this cased based on the Focused Time Delay Neural Network (FTDNN) for modeling the nonlinear system and performing the optimization procedure. In case of prediction and control, two individual strategies are concerned for the...

Computer text entry may be full of noises – for example, computer keyboard users inevitably make typing mistakes and their typing stream implies all users’ self rectification actions. These may produce a great negative influence on the accessibility and usability of applications. This research develops an original Intelligent Keyboard hybrid framework, which can be used to analyze users’ typing...

This paper aims to develop an artificial neural networkbased forecasting model employing a nonlinear focused time-delayed network (FTDNN) for energy commodity market forecasts. To validate the proposed model, crude oil and natural gas prices are used period 2007 2020, including Covid-19 period. Empirical findings show that FTDNN outperforms existing baselines models in West Texas Intermediate B...

Intelligent Universal Transformer (IUT) is a key point introducing as an Intelligent Electrical Devices (IED) for Advanced Distribution Automation (ADA) in future. ADA is the state of art, comprising flexible electrical architecture contributed with open communication construction for the tomorrow’s distribution automation. IUT is based on a power electronic transformer employing the new techno...

This paper is focused on the prediction and forecast of climate time series, particularly useful for planning and management of the power grid, by artificial neural networks. An appropriate prediction and forecast of climate variables, indeed, improves the overall efficiency and performance of renewable power plants connected to the power grid. On such a basis, the application of suitable Artif...

Phoneme classification and recognition is the first step to large vocabulary continuous speech recognition. This step represents the acoustic modeling part of such a system. In hybrid speech recognition systems phoneme recognition is made by artificial neural networks (ANN’s). The main objective of this paper is the investigation of dynamic ANN’s, namely the Time-Delay Neural Networks (TDNN) an...

Non-linear dynamical systems are difficult to control due to the model uncertainties and external disturbances that may occur in these systems. This paper addresses the problem of identification using dynamic neural networks (DNNs) based on genetic algorithm (GA) for nonlinear dynamic systems. Four different dynamic neural networks are used for identification of the same nonlinear dynamic syste...

Automatic Speaker Identification (ASI) is one of the active fields research in signal processing. Various machine learning algorithms have been used for this purpose. With recent developments hardware technologies and data accumulation, Deep Learning (DL) methods become new state-of-the-art approach several classification identification tasks. In paper, we evaluate performance traditional such ...