the quantitative structure-retention relationship (qsrr) of nanoparticles in roadside atmosphere against the comprehensive two-dimensional gas chromatography which was coupled to high-resolution time-of-flight mass spectrometry was studied. the genetic algorithm (ga) was employed to select the variables that resulted in the best-fitted models. after the variables were selected, the linear multi...

The objective of this study is to compare the predictive ability of Bayesian regularization with Levenberg–Marquardt Artificial Neural Networks. To examine the best architecture of neural networks, the model was tested with one-, two-, three-, four-, and five-neuron architectures, respectively. MATLAB (2011a) was used for analyzing the Bayesian regularization and Levenberg–Marquardt learning al...

the aim of this study was to estimate suspended sediment by the ann model, dt with cart algorithm and different types of src, in ten stations from the lorestan province of iran. the results showed that the accuracy of ann with levenberg-marquardt back propagation algorithm is more than the two other models, especially in high discharges. comparison of different intervals in models showed that r...

In the present work, an artificial neural network (ANN) model was used to study the quantitative structure retention relationship (QSRR) of retention index (RI) of some volatile compounds in natural cocoa and conched chocolate powder. Molecular structural descriptors are selected using genetic algorithm to construct the nonlinear QSRR models, kernel partial least squares PLS (KPLS) and Levenber...

Abstract— Electromyography (EMG) signal provides a significant source of information for identification of neuromuscular disorders. This paper presents an application of neural network classifier on classification and identification of different normal and auto aggressive actions of hands and legs. Eight features that are extracted from eight channel EMG signals representing these actions have ...

Back propagation neural network (BPNN) algorithm is a widely used technique in training artificial neural networks. It is also a very popular optimization procedure applied to find optimal weights in a training process. However, traditional back propagation optimized with Levenberg marquardt training algorithm has some drawbacks such as getting stuck in local minima, and network stagnancy. This...

Retrieving information from remotely sensed data is an important task. In the present work, data of L band microwave radiometer has been used to collect the brightness temperature over bare and vegetated fields in two polarizations at different moisture levels. Artificial neural network (ANN) trained with Levenberg-Marquardt algorithm has been used to determine soil moisture from brightness tem...

life style and life expectancy of inhabitants have been affected by the increase of particulate matter 10 micrometers or less in diameter (pm10) in cities and this is why maximum pm10 concentrations have received extensive attention. an early notice system for pm10 concentrations necessitates an accurate forecasting of the pollutant. in the current study an artificial neural network was used t...