The human brain contains at least 100 billion neurons, each with the ability to influence many other cells. Clearly, highly sophisticated and efficient mechanisms are needed to enable communication among this astronomical number of elements. Such communication is made possible by synapses, the functional contacts between neurons. The synapses have a major part to play for learning, memory and c...

A three-layer artificial neural network (ANN) model was developed to predict the remained DO (deoxygenation) in water after DO removal with an enzymatic granular biocatalyst (GB), based on the experimental data obtained in a laboratory stirring batch study. The effects of operational parameters such as initial pH, initial glucose concentration and temperature on DO removal were investigated. On...

In this study, a three–layer artificial neural network (ANN) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. A total of 455 data points were collected from 13 data sources to develop the ANN model. Superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of ...

We use artificial neural networks to perform curve prediction. For that, we have created a class of neural networks (feed forward multilayer perceptron networks with backpropagation) that have a topology which is determined by their genetic makeup. Using a simple evolutionary strategy on their genes, we optimise the networks’ topologies to solve the problems at hand. Using this approach, we cou...

In this study, a three–layer artificial neural network (ANN) model was developed to predict the pressure gradient in horizontal liquid–liquid separated flow. A total of 455 data points were collected from 13 data sources to develop the ANN model. Superficial velocities, viscosity ratio and density ratio of oil to water, and roughness and inner diameter of pipe were used as input parameters of ...

introduction according to the shortage of water resources in the world, it seems necessary the use of refined water, particularly in arid and semi-arid areas such as iran. the correct treatment, management and the control of refining process needs to investigate effective parameters in this process precisely. therefore, because of the uncertainty and complexity in refining qualitative parameter...

The prediction model for object-oriented software development effort estimation using one hidden layer neural network has been implemented in this paper. This prediction model has been empirically validated on PROMISE software engineering repository dataset. Accurate prediction of software development effort and schedule is still a challenging job in software industry. This prediction model has...

Abstract Erosion and sedimentation are the most complicated problems in hydrodynamic which are very important in water-related projects of arid and semi-arid basins. For this reason, the presence of suitable methods for good estimation of suspended sediment load of rivers is very valuable. Solving hydrodynamic equations related to these phenomenons and access to a mathematical-conceptual mode...

in this study, an artificial neural network was developed in order to analyze flexible pavement structure anddetermine its critical responses under the influence of standard axle loading. in doing so, more than 10000four-layered flexible pavement sections composed of asphalt concrete layer, base layer, subbase layer, andsubgrade soil were analyzed under the impact of standard axle loading. pave...

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...