Empirical Correlations and an Artificial Neural Network Approach to Estimate Saturated Vapor Pressure of Refrigerants
The examination of available vapor pressure data in the case of the methane, ethane, propane and butane halogenated refrigerants, allowed recommendations of standard equations for this property. In this study, three new models include a general correlation; a substance-dependent correlation and an artificial neural network (ANN) approach have been developed to estimate the saturated vapor pressure of refrigerants. With the presented approaches, vapor pressures have been calculated and compared with source data bank for 5600 data points of 28 refrigerants. The accuracies of new correlations and ANN have been compared with most commonly used correlations and the comparison indicates that all new models provide more accurate results than other literature correlations considered in this work.
empirical correlations and an artificial neural network approach to estimate saturated vapor pressure of refrigerants
the examination of available vapor pressure data in the case of the methane, ethane, propane and butane halogenated refrigerants, allowed recommendations of standard equations for this property. in this study, three new models include a general correlation; a substance-dependent correlation and an artificial neural network (ann) approach have been developed to estimate the saturated vapor press...متن کامل
today, scouring is one of the important topics in the river and coastal engineering so that the most destruction in the bridges is occurred due to this phenomenon. whereas the bridges are assumed as the most important connecting structures in the communications roads in the country and their importance is doubled while floodwater, thus exact design and maintenance thereof is very crucial. f...
Prediction of the Liquid Vapor Pressure Using the Artificial Neural Network-Group Contribution Method
In this paper, vapor pressure for pure compounds is estimated using the Artificial Neural Networks and a simple Group Contribution Method (ANN–GCM). For model comprehensiveness, materials were chosen from various families. Most of materials are from 12 families. Vapor pressure data of 100 compounds is used to train, validate and test the ANN-GCM model. Va...متن کامل
Application of statistical techniques and artificial neural network to estimate force from sEMG signals
This paper presents an application of design of experiments techniques to determine the optimized parameters of artificial neural network (ANN), which are used to estimate force from Electromyogram (sEMG) signals. The accuracy of ANN model is highly dependent on the network parameters settings. There are plenty of algorithms that are used to obtain the optimal ANN setting. However, to the best ...متن کامل
This study shows the usefulness of Artificial Neural Network (ANN) in maintenance planning and man-agement. An ANN model based on the multi-layer perceptron having three hidden layers and four processing elements per layer was built to predict the expected downtime resulting from a breakdown or a maintenance activity. The model achieved an accuracy of over 70% in predicting the expected downtime.متن کامل
An artificial Neural Network approach to monitor and diagnose multi-attribute quality control processes
One of the existing problems of multi-attribute process monitoring is the occurrence of high number of false alarms (Type I error). Another problem is an increase in the probability of not detecting defects when the process is monitored by a set of independent uni-attribute control charts. In this paper, we address both of these problems and consider monitoring correlated multi-attributes proce...متن کامل
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دوره 5 شماره 2
صفحات 281- 292
تاریخ انتشار 2017-06-01
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