In recent years, an explosion in research on pattern recognition systems using neural network methods has been observed. Face Recognition (FR) is a specialized pattern recognition task for several applications such as security: access to limited areas, banking: identity confirmation and identification of wanted people at airports. Biometric techniques deals with identifying individual with the ...

In this work, adaptive learning of a monitored real-time stochastic phenomenon over an operational LTE broadband radio network interface is proposed using cascade forward neural (CFNN) model. The optimal architecture the model has been implemented computationally in input and hidden units by means incremental search process. Particularly, we have applied adaptive-based cascaded for realistic pr...

The bulk of water pipes experience major degradation and deterioration problems. This research aims at estimating the condition in Shattora Shaker Al-Bahery’s distribution networks, Egypt. developed models involve training Elman neural network (ENN) feed-forward (FFNN) coupled with particle swarm optimization (PSO), genetic algorithms (GA), sine cosine algorithm (SCA), teaching-learning-based (...

Unlike feedforward neural networks (FFNN) which can act as universal function approximaters, recursive neural networks have the potential to act as both universal function approximaters and universal system approximaters. In this paper, a globally recursive neural network least mean square (GRNNLMS) gradient descent or a real time recursive backpropagation (RTRBP) algorithm is developed for a s...

In this paper, we show how Bayesian neural networks can be used for time series analysis. We consider a block based model building strategy to model linear and nonlinear features within the time series. A proposed model is a linear combination of a linear autoregression term and a feedforward neural network (FFNN) with an unknown number of hidden nodes. To allow for simpler models, we also cons...

Early residential fire detection is important for prompt extinguishing and reducing damages and life losses. To detect fire, one or a combination of sensors and a detection algorithm are needed. The sensors might be part of a wireless sensor network (WSN) or work independently. The previous research in the area of fire detection using WSN has paid little or no attention to investigate the optim...

Direct Sequence Code Division Multiple Access (DS-CDMA) is a schemewhere several users transmit their data simultaneously over common wireless communication channel,by spreading each by distinct codes. At the receiver, individual are detected appropriate decoding. In this paper, new smart receiver proposed for detecting DS-CDMA signals based on multi-layer Feed Forward Neural Network (FFNN). Th...

Abstract The present study uses a wavelet-based clustering technique to identify spatially homogeneous clusters of groundwater quantity and quality data select the most effective input for feed-forward neural network (FFNN) model predict level (GL), pH HCO3? in groundwater. In second stage this methodology, first, GL, time series different piezometers were de-noised using threshold-based wavele...

Production of highly viscous tar sand bitumen using Steam Assisted Gravity Drainage (SAGD) with a pair of horizontal wells has advantages over conventional steam flooding. This paper explores the use of Artificial Neural Networks (ANNs) as an alternative to the traditional SAGD simulation approach. Feed forward, multi-layered neural network meta-models are trained through the Back-...