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...

In this paper, the estimation capacities of the response surface methodology (RSM) and artificial neural network (ANN), in a microwave-assisted extraction method to determine the amount of zinc in fish samples were investigated. The experiments were carried out based on a 3-level, 4-variable Box-Behnken design. The amount of zinc was considered as a function of four independent variables, namel...

The results of two alternative models to predict segmental durations in speech synthesis, both based on Artificial Neural Networks (ANNs) are discussed. The ANN model consists in just one ANN trained to predict the segmental durations for all phonemes. The phoneme dedicated ANN model consists in a set of ANNs, each one dedicated to predict the segmental duration of a specific phoneme. Both mode...

in this research, a two-phase algorithm based on the artificial neural network (ann) and a harmony search (hs) algorithm has been developed with the aim of assessing the reliability of structures with implicit limit state functions. the proposed method involves the generation of datasets to be used specifically for training by finite element analysis, to establish an ann model using a proven an...

in the present work, the influences of temperature, solvent concentration and ultrasonic irradiation time were numerically analyzed on viscosity reduction of residue fuel oil (rfo). ultrasonic irradiation was applied at power of 280 w and low frequency of 24 khz. the main feature of this research is prediction and optimization of the kinematic viscosity data. the measured results of eighty-four...

Due to various seasonal and monthly changes in electricity consumption and difficulties in modeling it with the conventional methods, a novel algorithm is proposed in this paper. This study presents an approach that uses Artificial Neural Network (ANN), Principal Component Analysis (PCA), Data Envelopment Analysis (DEA) and ANOVA methods to estimate and predict electricity demand for seasonal a...

Today self-organization and automatic usage of Artificial Neural Networks (ANN) are common in various applications for financial services providers. We analyze typical advantages and disadvantages of ANN and discuss the question: For which tasks ANN applications are most promising? We show that Intelligent Decision Support Systems (IDSS) based on ANN and Neurosimulators can support today’s comp...

Introduction: The possibility of depression is common in the elderly. Novel technologies allow us to monitor people related to depression. Hence, a model was provided to detect depression in elderly based on artificial neural network (ANN). Methods: The present study is an applied descriptive-survey research. Forty elderly people were randomly selected from the Elderly Care Center in Gonbad Ka...

nowadays, it has demonstrated that viruses can be transmitted by water and foods. therefore, it causes the research to develop for detecting different viruses in water and foods. among foods, milk can transfer potentially pathogenic viruses. on the other hand, to achieve every method for recovery and extraction of viruses in raw milk it needs to know about impact of milk components on viruses. ...

one of the main aims of water resource planners and managers is to estimate and predict the parameters of groundwater quality so that they can make managerial decisions. in this regard, there have many models developed, proposing better management in order to maintain water quality. most of these models require input parameters that are either hardly available or time-consuming and expensive to...