Prediction of Atmospheric Pressure is one important and challenging task that needs lot of attention and study for analyzing atmospheric conditions. Advent of digital computers and development of data driven artificial intelligence approaches like Artificial Neural Networks (ANN) have helped in numerical prediction of pressure. However, very few works have been done till now in this area. The p...

This study presents an integrated Artificial Neural Network (ANN) and time series framework to estimate and predict Signal to Interference Ratio (SIR) in Direct Sequence Code Division Multiple Access (DS/CDMA) systems. It is difficult to model uncertain behavior of SIR with only conventional ANN or time series and the integrated algorithm could be an ideal substitute for such cases. Artificial ...

This paper presents artificial neural network (ANN)-based models for forecasting precipitation, in which the training parameters are adjusted using a parameter automatic calibration (PAC) approach. A classical ANN-based model, the multilayer perceptron (MLP) neural network, was used to verify the utility of the proposed ANN–PAC approach. The MLP-based ANN used the learning rate, momentum, and n...

An adaptive neural network backstepping control for a class of uncertain nonlinear systems is presented in this paper. Three main issues will be treated: (1) unknown nonlinearities; (2) unknown system parameters; (3) external or internal disturbances. The proposed technique is applied to a simple pendulum. This latter is an unstable system which is perfectly described by a nonlinear model obtai...

Abstract—Human beings have the ability to make logical decisions. Although human decision making is often optimal, it is insufficient when huge amount of data is to be classified. Medical dataset is a vital ingredient used in predicting patient’s health condition. In other to have the best prediction, there calls for most suitable machine learning algorithms. This work compared the performance ...

Data mining is an essential phase in knowledge discovery in database which is actually used to extract hidden patterns from large databases. Data mining concepts and methods can be applied in various fields like marketing, medicine, real estate, customer relationship management, engineering, web mining, etc. The main objective of this paper is to compare the performance accuracy of Multilayer p...

the main purpose of this paper is prediction of tse corporate financial bankruptcy using artificial neural networks. the mean values of key ratios reported in past bankruptcy studies were selected for neural network inputs (working capital to total assets, net income to total assets, total debt to total assets, current assets to current liabilities, quick assets to current liabilities). the neu...

This paper designs a reconfigurable 5-fingers microstrip patch antenna using artificial neural networks (ANNs). The particular neural networks selected for this task are the source difference method (SD), multilayer perceptron (MLP), prior knowledge input method (PKI) and difference prior knowledge input method (PKID). Employing fine and coarse models for training the networks enables to develo...

in this study, using sound created by wheat grain passing through a pipe, wheat flow rate was measured. the developed device consists of a hopper, metering device, sound sensor, delivery tube, dc motor and power supply. several wheat mass flow rates were tested and the sound signal created by the passage of the grain through the discharge tube was measured and transferred to a computer using da...

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...