The artificial neural networks, the learning algorithms and mathematical models mimicking the information processing ability of human brain can be used non-linear and complex data. The aim of this study was to predict the breeding values for milk production trait in Iranian Holstein cows applying artificial neural networks. Data on 35167 Iranian Holstein cows recorded between 1998 to 2009 were ...

In this paper, a new Transform Domain implementation of the well known Multilayer Perceptron Neural Network is presented. With the Transform Domain implementation, the input of the Neural Network can be represented in a more compact manner and the elements of the input vector become uncorrelated. The new Transform Domain Multilayer Perceptron (TDMLP) Neural Network is applied for the problem of...

The approach to the design of direct current (DC) motor varies considerably using advanced methods such as artificial intelligence (AI). However, accuracy issues cannot be totally addressed using conventional methods. This paper presents the study on nonlinear autoregressive moving average with exogenous input (NARMAX) model using multilayer perceptron (MLP) neural network for DC motor modeling...

Rainfall-runoff relationship is very important in many fields of hydrology such as water supply and water resourcemanagement and there are many models in this field. Among these models, the Artificial Neural Network (ANN) wasfound suitable for processing rainfall-runoff and opened various approaches in hydrological modeling. In addition,ANNs are quick and flexible approaches which provide very ...

The goal of this paper is to compare and analyze the forecasting performance of two artificial neural network models (i.e., MLP (multi-layer perceptron) and DNN (deep neural network)), and to conduct an experimental investigation by data flow, not economic flow. In this paper, we investigate beyond the scope of simple predictions, and conduct research based on the merits and data of each model,...

A signal su ers from nonlinear, linear, and additive distortion when transmitted through a channel. Linear equalizers are commonly used in receivers to compensate for linear channel distortion. As an alternative, nonlinear equalizers have the potential to compensate for all three sources of channel distortion. Previous authors have shown that nonlinear feedforward equalizers based on either mul...

Problem statement: The synthesis of a command by the neural network has an excellent advantage over the classical one such as PID. This study presented a fast and accurate Wavelet Neural Network (WNN) approach for efficient controlling of an Active Magnetic Bearing (AMB) system. Approach: The proposed approach combined neural network with the wavelet theory. Wavelet theory may be exploited in d...

Background: Intracytoplasmic sperm injection (ICSI) or microinjection is one of the most commonly used assisted reproductive technologies (ART) in the treatment of patients with infertility problems. At each stage of this treatment cycle, many dependent and independent variables may affect the results, according to which, estimating the accuracy of fertility rate for physicians will be difficul...

In this paper, it is shown that Multilayer perceptron Neural Network can elegantly perform nonlinear regression of transfer characteristic of electronic devices. After rigorous computer simulations authors develop the optimal MLP NN models, which elegantly perform such a nonlinear regression. Results show that the proposed optimal MLP NN models have optimal values of MSE (mean square error), r ...