The purpose of this study is to analyze the performance of Back propagation algorithm with changing training patterns and the second momentum term in feed forward neural networks. This analysis is conducted on 250 different words of three small letters from the English alphabet. These words are presented to two vertical segmentation programs which are designed in MATLAB and based on portions (1...

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...

Due to lack of theory of elasticity, estimation of ultimate torsional strength of reinforcement concrete beams is a difficult task. Therefore, the finite element methods could be applied for determination of strength of concrete beams. Furthermore, for complicated, highly nonlinear and ambiguous status, artificial neural networks are appropriate tools for prediction of behavior of such states. ...

In this paper we first show that standard BP algorithm cannot yeild to a uniform information distribution over the neural network architecture. A measure of sensitivity is defined to evaluate fault tolerance of neural network and then we show that the sensitivity of a link is closely related to the amount of information passes through it. Based on this assumption, we prove that the distribu...

Rainfall-runoff modeling in ungauged basins continues to be a great hydrological research challenge. A novel approach is the Long-Short-Term-Memory neural network (LSTM) from Deep Learning toolbox, which few works have addressed its use for rainfall-runoff regionalization. This work aims discuss application of LSTM as regional method against traditional (FFNN) and conceptual models practical fr...

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...

This study was conducted to investigate the prediction of growth performance using linear regression and artificial neural network (ANN) in broiler chicken. Artificial neural networks (ANNs) are powerful tools for modeling systems in a wide range of applications. The ANN model with a back propagation algorithm successfully learned the relationship between the inputs of metabolizable energy (kca...