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Open Access. Powered by Scholars. Published by Universities.®

2023

Artificial Neural Network (ANN)

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Full-Text Articles in Engineering

An Artificial Neural Network Approach To Predicting Formation Stress In Multi-Stage Fractured Marcellus Shale Horizontal Wells Based On Drilling Operations Data, Moudhi Alawadh Jan 2023

An Artificial Neural Network Approach To Predicting Formation Stress In Multi-Stage Fractured Marcellus Shale Horizontal Wells Based On Drilling Operations Data, Moudhi Alawadh

Graduate Theses, Dissertations, and Problem Reports

The distribution of the anisotropic minimum horizontal stress, both in horizontal and vertical directions, is necessary for effective hydraulic fracture treatment design in Marcellus Shale horizontal wells. Typically, the minimum horizontal stress can be estimated sonic logs. However, sonic log data is not commonly available for the horizontal Marcellus shale wells due to the complexity and cost. The objective of this research is to predict the anisotropic minimum horizontal stress by utilizing drilling parameters including depth, weight-on-bit (WOB), revolution per minute (RPM), standpipe pressure, torque, pump flow rate, and the rate of penetration (ROP). More specifically, artificial neural network (ANN) …

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Microstrip Antenna Design Using Cst Optimized By Neural Network Algorithm, Hadeer. A Shoeab, Mohamed A.Mohamed, Marzouk El Said A, Ahmed. A. Kabeel Jan 2023

Microstrip Antenna Design Using Cst Optimized By Neural Network Algorithm, Hadeer. A Shoeab, Mohamed A.Mohamed, Marzouk El Said A, Ahmed. A. Kabeel

Mansoura Engineering Journal

In this paper, a general design procedure is suggested for the microstrip antennas using artificial neural networks and this is demonstrated using the rectangular patch geometry. The model was analyzed for 1733 data sets of input output parameters. 1300 samples for training and 433 samples for testing and 1500 epoch, learning rate from (0.003 to 0.005). Python was used to create and implement the ANN algorithm model. The mean error in detection of resonance frequencies (return loss peaks) was 0.144GHz on train set, and 0.116GHz on test set. The outputs of the radial basis function are optimized by varying the …

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