Objective(s): This study aims to evaluate and predict the thermal conductivity of iron oxide nanofluid at different temperatures and volume fractions by artificial neural network (ANN) and correlation using experimental data. Methods: Two-layer perceptron feedforward artificial neural network and backpropagation Levenberg-Marquardt (BP-LM) tra...

In the paper, we study the problems of nearest neighbor queries (NN) and all nearest neighbor queries (ANN) on location data, which have a wide range of applications such as Geographic Information System (GIS) and Location based Service (LBS). We propose a new structure, termed AVR-Tree, based on the R-tree and Voronoi diagram techniques. Compared with the existing indexing techniques used for ...

conclusions the present study detected more accurate results for ann method compared to those of cox ph model to analyze the survival of patients with liver transplantation. furthermore, the order of effective factors in patients’ survival after transplantation was clinically more acceptable. the large dataset with a few missing data was the advantage of this study, the fact which makes the res...

The study area, located in the southern section of the Central Iranian volcano–sedimentary complex, contains a large number of mineral deposits and occurrences which is currently facing a shortage of resources. Therefore, the prospecting potential areas in the deeper and peripheral spaces has become a high priority in this region. Different direct and indirect methods try to predict promising a...

investigating the export function of border markets in iran, using the ann approach ali falahati faculty of economics razi university of kerman minoo nazifi naeini sahar abbaspour abstract nowadays, trade has been introduced as an engine of growth and development in developing countries so states are required to participate in international trade more seriously. one way for expanding participat...

In this study, we propose a new Artificial Neural Networks (ANN) training approach that closes the gap between ANN and Data Envelopment Analysis (DEA), and has the advantage of giving similar results to DEA and being easier to compute. Our method is based on extreme point selection in a bandwidth while determining the training set, and it gives better results than the traditional ANN approach. ...

Bayesian methods are a kind of data-driven methods developed in recent years and have played an important role in fault detection and diagnosis. Nevertheless, traditional Bayesian fault detection methods cannot deal with the case where some underlying modes are ambiguous in the historical data. To cope with this problem, a new method is presented in this paper. The modes with uncertainty in his...

Forecasting financial markets is an important issue in finance area and research studies. On one hand, the importance of prediction, and on the other hand, its complexity, have led to huge number of researches which have proposed many forecasting methods in this area. In this study, we propose a hybrid model including Wavelet Transform, ARMA-GARCH and Artificial Neural Network (ANN) for single-...