Equations of state are useful for description of fluid properties such as pressure-volumetemperature (PVT). However, the success estimation of such correlations depends mainly on the range of data which have originated. Therefore new models are highly required. In this work a new method is proposed based on Artificial Neural Network (ANN) for estimation of PVT properties of compounds. The data ...

We present a new learning algorithm for the supervised training of multilayer perceptrons for classification that is significantly faster than any previously known method. Like existing methods, the algorithm assumes a multilayer perceptron with a normalized exponential (softmax) output trained under a cross-entropy criterion. However, this output-criteria pairing turns out to have poor propert...

This study develops a new approach for forecasting shear Strength of concrete beam without stirrups based on the artificial neural networks (ANN). Proposed ANN considers geometric and mechanical properties of cross section and FRP bars, and shear span-depth ratio. The ANN model is constructed from a set of experimental database available in the past literature. Efficiency of the ANN model was c...

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...

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...

recently, hardware sensors are widely used in monitoring and measurement of water quality parameters. constraint of the instrument to measure some water quality parameters such as the 5-day biochemical oxygen demand (bod5), which are time consuming, causes efforts are diverted to the use of software sensors for online prediction of bod5. the main goal of this research is developing an appropria...

In this study, a Neural Network (NN) based data fusion and estimation algorithm is developed, which could be applied in monitoring and detection applications that use measurements coming from multiple sensors. For NN based applications, a fast training approach which can also guarantee the global minimum is highly desirable and is subject for ongoing research. For this purpose, in this study, a...

Artificial Neural Network (ANN) which is designed to mimic the human brain have been used in the literature for identifying variable(s) that is(are) responsible for out-of-control signal and the training algorithms have played a significant role in the identification of the aberrant variable(s). In this paper the effect of three algorithms in the training of ANN for pattern recognition of bivar...

This paper presents an indoor positioning technique based on a multi-layer feed-forward (MLFF) artificial neural networks (ANN). Most of the indoor received signal strength (RSS)-based WLAN positioning systems use the fingerprinting technique that can be divided into two phases: the offline (calibration) phase and the online (estimation) phase. In this paper, RSSs were collected for all referen...

In recent years, due to vital need for novel fungicidal agents, investigation on natural antifungal resources has been increased. The special features exhibited by neural network classifiers make them suitable for handling complex problems like analyzing different properties of candidate compounds in computer-aided drug design. In this study, by using a Levenberg-Marquardt (LM) neural network (...