abstract agricultural sector is the most important sectors in the country which has a large share in total employment. the increasing supply of labor because population growth and low capacity of production cause the country with high rate of unemployment. therefore, stand with this crisis is one of the most important works of government. in this study using artificial neural network, the emplo...

Artificial Neural Networks (ANN) have gained increasing popularity as an alternative to statistical methods for classification of Remote Sensing Data. Their superiority to some of the classical statistical methods has been shown in the literature. Therefore, ANNs are commonly used for segmentation and classification purposes. In this paper we address a land cover classification problem using mu...

Trajectory tracking is an essential capability of robotics operation in industrial automation. In this article, an artificial neural controller is proposed to tackle trajectory-tracking problem of an autonomous ground vehicle (AGV). The controller is implemented based on fractional order proportional integral derivative (FOPID) control that was already designed in an earlier work. A non-holonom...

drought is random and nonlinear phenomenon and using linear stochastic models, nonlinear artificial neural network and hybrid models is advantaged for drought forecasting. this paper presents the performances of autoregressive integrated moving average (arima), direct multi-step neural network (dmsnn), recursive multi-step neural network (rmsnn), hybrid stochastic neural network of directive ap...

In this study, a method based on using image processing and artificial neural network is introduced to determine pelt color and curl size of newborn lambs in Zandi sheep. The data was collected from 300 newborn lambs reared in the Zandi sheep breeding centre of Khojir, Tehran. Primarily, curl size and pelt color of new born lambs was recorded by experienced appraisers, and at the same time, sev...

With the work at hand we want to present a model of a neural system, that is influenced by emotions. This model is based on the state of the art concept of artificial neural networks (ANN) which we improve by adding ‘artificial emotions’. The way of the implementation of emotions is based on the research results regarding the biological and biochemical processes modulating neural cells in anima...

In this paper, we propose an intelligent first-warning system for virus code detection based on Artificial Neural Networks (ANNs). The proposed system operates in accordance with the basic principles of ANNs to conduct pattern matching of 32-bit hash signatures and detect virus signatures by means of the hashing applied to the byte content of executable code. The proposed system can accurately ...

Artificial Neural networks (ANNs) have been extensively used in many signal processing applications. Linear & Nonlinear adaptive filters based on a variety of neural network models have been used successfully for system identification in a wide range of applications. Due to their capacity to form complex decision regions, ANNs have been most popularly applied, in particular, for channel equaliz...

Artificial neural networks (ANNs), especially when they have feedback connections, are potentially able to produce complex dynamics, and therefore have received attention in control applications. Although ANNs are powerful, designing a network can be a difficult task, and the more complex desired dynamics are, the more difficult the design of the network becomes. Many researchers have sought to...

An artificial neural network has been used to determine the volume flux and rejections of Ca2+ , Na+ and Cl¯, as a function of transmembrane pressure and concentrations of Ca2+, polyethyleneimine, and polyacrylic acid in water softening by nanofiltration process in presence of polyelectrolytes. The feed-forward multi-layer perceptron artificial neural network including an eight-neuron hidde...