Permeability Prediction Using Artificial Neural Network (ANN): A Case Study of Uinta Basin

2005 ◽  
Author(s):  
S. Singh
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Uinta Basin ◽  
Permeability Prediction ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

scholarly journals Artificial Neural Network Trained to Predict High-Harmonic Flux

2018 ◽  
Vol 8 (11) ◽  
pp. 2106 ◽  
Author(s):  
Ana Gherman ◽  
Katalin Kovács ◽  
Mircea Cristea ◽  
Valer Toșa
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
High Harmonic ◽  
Ann Model ◽  
Dimensional Parameter ◽  
High Order Harmonic ◽  
Cell Position ◽  
Artificial Neural ◽  
Artificial Neural Network Ann

In this work we present the results obtained with an artificial neural network (ANN) which we trained to predict the expected output of high-order harmonic generation (HHG) process, while exploring a multi-dimensional parameter space. We argue on the utility and efficiency of the ANN model and demonstrate its ability to predict the outcome of HHG simulations. In this case study we present the results for a loose focusing HHG beamline, where the changing parameters are: the laser pulse energy, gas pressure, gas cell position relative to focus and medium length. The physical quantity which we predict here using ANN is directly related to the total harmonic yield in a specified spectral domain (20–40 eV). We discuss the versatility and adaptability of the presented method.

scholarly journals Design of an Artificial Neural Network (BPNN) to Predict the Content of Silicon Oxide (SiO2) based on the Values of the Rock Main Oxides: Glass Factory Feed Case Study

2022 ◽  
Vol 11 (02) ◽  
pp. 41-44
Author(s):  
Hamed Nazerian ◽  
Adel Shirazy ◽  
Aref Shirazi ◽  
Ardeshir Hezarkhani
Keyword(s):  
Neural Network ◽  
Artificial Neural Network ◽  
Silicon Oxide ◽  
Back Propagation ◽  
Back Propagation Neural Network ◽  
Neural Network Algorithm ◽  
Artificial Neural ◽  
Artificial Neural Network Ann ◽  
Artificial Neural Network Algorithm

Artificial neural network (ANN) is one of the practical methods for prediction in various sciences. In this study, which was carried out on Glass and Crystal Factory in Isfahan, the amount of silica purification used in industry has been investigated according to its analyses. In this discussion, according to the artificial neural network algorithm back propagation neural network (BPNN), the amount of silica (SiO2) was predicted according to rock main oxides in chemical analysis. These studies can be used as a criterion for estimating the purity for use in the factory due to the high accuracy obtained.

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