Cox regression model serves as a statistical method for analyzing the survival data, which requires some options such as hazard proportionality. In recent decades, artificial neural network model has been increasingly applied to predict survival data. This research was conducted to compare Cox regression and artificial neural network models in prediction of kidney transplant survival. The prese...

In the present study, two different data-driven models, artificial neural network (ANN) and multiple linear regression (MLR) models, have been developed to predict the 28 days compressive strength of concrete. Seven different parameters namely 3/4 mm sand, 3/8 mm sand, cement content, gravel, maximums size of aggregate, fineness modulus, and water-cement ratio were considered as input variables...

this paper presents a new model for predicting the compressive strength of steel-confined concrete on circular concrete filled steel tube (ccfst) stub columns under axial loading condition based on artificial neural networks (anns) by using a large wide of experimental investigations. the input parameters were selected based on past studies such as outer diameter of column, compressive strength...

introduction: intravenous general anesthetic agents are among the most important and widely used anesthetic drugs in the clinical practice. many pharmacological studies have shown that potentiation of gaba and glycine on their receptors is the most plausible mechanism. nevertheless, there is limited information on the effects of co-administration of two or more of these agents. however, experim...

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...

This thesis describes an attempt to predict the next value in a financial time series using various artificial techniques. The time series in question consists of daily values for commodities futures. First, an artificial neural network is used as a predictor. Then the neural network is augmented with a genetic algorithm. The genetic algorithm first is used to select the parameters for the neur...

The purpose of this study is designing a model based on Tobit regression, DEA, Artificial Neural Network, Genetic Algorithm and Particle Swarm Optimization to evaluate the efficiency and also benchmarking the efficient and inefficient units. This model has three stages, and it uses the data envelopment analysis combined model with neural network, optimized by genetic algorithm, to evaluate the ...

introduction rainfall is considered as one of the most important factures in water cycle. prediction of monthly rainfall is important for many purposes such as estimating torrent, drought, run-off, sediment, irrigation programming and also management of drainage basins. rainfall prediction in each area is mediated by punctual data measured as humidity, temperature, wind speed and etc. as iran i...