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...

A new method for extracting the Brillouin frequency shift (BFS) from gain spectrum (BGS), modified backward correlation (MBWC), is presented. The possibilities of using MBWC, and MBWC in combination with Lorentzian curve fitting (LCF) based on Levenberg–Marquardt (LM) method, are studied. effectiveness its LM, has been demonstrated processing spectra a low signal-to-noise ratio (SNR). experimen...

The Levenberg-Marquardt (LM) gradient descent algorithm is used extensively for the training of Artificial Neural Networks (ANN) in the literature, despite its limitations, such as susceptibility to the local minima that undermine its robustness. In this paper, a bioinspired algorithm referring to the Bat algorithm was proposed for training the ANN, to deviate from the limitations of the LM. Th...

This paper presents an innovative method to evaluate the credibility of network connections based on neural network with back propagation (BP) network model and Levenberg-Marquardt (LM) optimization algorithm. In it, the second-level index values are taken as input and expected evaluation values as output, based on which, L test samples are used to test the trained neural network. At last, a pr...

This paper presents the development of an artificial neural network (ANN) model based on the multi-layer perceptron (MLP) for analyzing internet traffic data over IP networks. We applied the ANN to analyze a time series of measured data for network response evaluation. For this reason, we used the input and output data of an internet traffic over IP networks to identify the ANN model, and we st...

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 (...

This paper proposes a hybrid intelligent model for runoff prediction. The proposed model is a combination of data preprocessing methods, genetic algorithms and levenberg–marquardt (LM) algorithm for learning feed forward neural networks. Actually it evolves neural network initial weights for tuning with LM algorithm by using genetic algorithm. We also use data pre-processing methods such as dat...

We describe a technique for solving for the orbital elements of multiple planets from radial velocity (RV) and/or astrometric data taken with 1 m/s and μas precision, appropriate for efforts to detect Earth-massed planets in their stars’ habitable zones, such as NASA’s proposed Space Interferometry Mission. We include details of calculating analytic derivatives for use in the Levenberg-Marquard...

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 ...