1-20 of 101
Neural networks
Close
Save search
Follow your search
Access your saved searches in your account
Would you like to receive an alert when new items match your search?
Close Modal
Sort by
Proceedings Papers

Preliminary Blast Fragmentation Modeling in an Underground Aggregate Operation

Available to Purchase

L. Shields, J. Calnan, J. Silva, E. Maldonado, Z. Agioutantis
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0053
https://doi.org/10.56952/ARMA-2024-0053
Add To Cart
View Paper titled, Preliminary Blast Fragmentation Modeling in an Underground Aggregate Operation
Open the PDF for Preliminary Blast Fragmentation Modeling in an Underground Aggregate Operation in another window
Add to Citation Manager for Preliminary Blast Fragmentation Modeling in an Underground Aggregate Operation
Proceedings Papers

Surrogate-Based Hydraulic Fracture Propagation Prediction Using Deep Neural Network Proxy

Available to Purchase

Fan Li, Yayun Zhang, Cong Xiao
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0056
https://doi.org/10.56952/ARMA-2024-0056
Add To Cart
View Paper titled, Surrogate-Based Hydraulic Fracture Propagation Prediction Using Deep Neural Network Proxy
Open the PDF for Surrogate-Based Hydraulic Fracture Propagation Prediction Using Deep Neural Network Proxy in another window
Add to Citation Manager for Surrogate-Based Hydraulic Fracture Propagation Prediction Using Deep Neural Network Proxy
Proceedings Papers

Chipping Mechanisms in Rotary-Percussive Drilling: Experimental Insights into the Role of the Median Crack as Precursor of the Dynamic Fragmentation Process

Available to Purchase

J. Aising, L. Gerbaud, H. Sellami, P. Senechal, P. Moonen, I. Ugarte
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0835
https://doi.org/10.56952/ARMA-2024-0835
Add To Cart
View Paper titled, Chipping Mechanisms in Rotary-Percussive Drilling: Experimental Insights into the Role of the Median Crack as Precursor of the Dynamic Fragmentation Process
Open the PDF for Chipping Mechanisms in Rotary-Percussive Drilling: Experimental Insights into the Role of the Median Crack as Precursor of the Dynamic Fragmentation Process in another window
Add to Citation Manager for Chipping Mechanisms in Rotary-Percussive Drilling: Experimental Insights into the Role of the Median Crack as Precursor of the Dynamic Fragmentation Process
Proceedings Papers

Progressive Reduced Order Modeling: From Single-Phase Flow to Coupled Multiphysics Processes

Available to Purchase

Teeratorn Kadeethum, Kyung Won Chang, John D. Jakeman, Hongkyu Yoon
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0096
https://doi.org/10.56952/ARMA-2024-0096
Add To Cart
View Paper titled, Progressive Reduced Order Modeling: From Single-Phase Flow to Coupled Multiphysics Processes
Open the PDF for Progressive Reduced Order Modeling: From Single-Phase Flow to Coupled Multiphysics Processes in another window
Add to Citation Manager for Progressive Reduced Order Modeling: From Single-Phase Flow to Coupled Multiphysics Processes
Proceedings Papers

Multi-Source Data Fusion and Knowledge Presentation for Shield Tunnel Maintenance Work Based on Knowledge Graph

Available to Purchase

H. J. Pang, C. C. Zha, F. Jia, Y. D. Xue
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0876
https://doi.org/10.56952/ARMA-2024-0876
Add To Cart
View Paper titled, Multi-Source Data Fusion and Knowledge Presentation for Shield Tunnel Maintenance Work Based on Knowledge Graph
Open the PDF for Multi-Source Data Fusion and Knowledge Presentation for Shield Tunnel Maintenance Work Based on Knowledge Graph in another window
Add to Citation Manager for Multi-Source Data Fusion and Knowledge Presentation for Shield Tunnel Maintenance Work Based on Knowledge Graph
Proceedings Papers

Real-Time Rate of Penetration Prediction for Motorized Bottom Hole Assembly Using Artificial Intelligence

Available to Purchase

Amir Shokry Youssef, Salaheldin Elkatatny, Abdulazeez Abdulraheem, Idham Rahmatullah
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-1059
https://doi.org/10.56952/ARMA-2024-1059
Add To Cart
View Paper titled, Real-Time Rate of Penetration Prediction for Motorized Bottom Hole Assembly Using Artificial Intelligence
Open the PDF for Real-Time Rate of Penetration Prediction for Motorized Bottom Hole Assembly Using Artificial Intelligence in another window
Add to Citation Manager for Real-Time Rate of Penetration Prediction for Motorized Bottom Hole Assembly Using Artificial Intelligence
Proceedings Papers

Drilling Data Based Approach for Real-Time Gamma Ray Prediction in Surface Holes Using Artificial Intelligence

Available to Purchase

Amir Shokry Youssef, Salaheldin Elkatatny, Abdulazeez Abdulraheem
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-1057
https://doi.org/10.56952/ARMA-2024-1057
Add To Cart
View Paper titled, Drilling Data Based Approach for Real-Time Gamma Ray Prediction in Surface Holes Using Artificial Intelligence
Open the PDF for Drilling Data Based Approach for Real-Time Gamma Ray Prediction in Surface Holes Using Artificial Intelligence in another window
Add to Citation Manager for Drilling Data Based Approach for Real-Time Gamma Ray Prediction in Surface Holes Using Artificial Intelligence
Proceedings Papers

Enhancing Joint Detection and RQD Estimation in Acoustic Televiewer Imaging Through Automated Instance Segmentation and Deep Learning

Available to Purchase

N. Houshmand, K. Esmaeili, S. Goodfellow
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-1047
https://doi.org/10.56952/ARMA-2024-1047
Add To Cart
View Paper titled, Enhancing Joint Detection and RQD Estimation in Acoustic Televiewer Imaging Through Automated Instance Segmentation and Deep Learning
Open the PDF for Enhancing Joint Detection and RQD Estimation in Acoustic Televiewer Imaging Through Automated Instance Segmentation and Deep Learning in another window
Add to Citation Manager for Enhancing Joint Detection and RQD Estimation in Acoustic Televiewer Imaging Through Automated Instance Segmentation and Deep Learning
Proceedings Papers

Artificial Neural Network for the Prediction of Unconfined Compressive Strength of Ultra Lightweight Cement for Oil and Gas Wells

Available to Purchase

A. D. Addo-Yobo, A. Hussain, H. Emadi, E. Maslowski de Moraes, M. Watson
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-1109
https://doi.org/10.56952/ARMA-2024-1109
Add To Cart
View Paper titled, Artificial Neural Network for the Prediction of Unconfined Compressive Strength of Ultra Lightweight Cement for Oil and Gas Wells
Open the PDF for Artificial Neural Network for the Prediction of Unconfined Compressive Strength of Ultra Lightweight Cement for Oil and Gas Wells in another window
Add to Citation Manager for Artificial Neural Network for the Prediction of Unconfined Compressive Strength of Ultra Lightweight Cement for Oil and Gas Wells
Proceedings Papers

Analysis of Influencing Factors of Fracturing Effect Based on Artificial Neural Network

Available to Purchase

C. Lu, J. H. Sun, Y. Li, M. Li, J. Q. Liu, Q. Y. Zhu, Q. Y. Li, Q. J. Zeng, S. X. Wang
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-1136
https://doi.org/10.56952/ARMA-2024-1136
Add To Cart
View Paper titled, Analysis of Influencing Factors of Fracturing Effect Based on Artificial Neural Network
Open the PDF for Analysis of Influencing Factors of Fracturing Effect Based on Artificial Neural Network in another window
Add to Citation Manager for Analysis of Influencing Factors of Fracturing Effect Based on Artificial Neural Network
Proceedings Papers

Real-Time Prediction of Potential Hazard Area in Seville's During Underground Excavation with EPB

Available to Purchase

Maziyar Bahri, Sebnem Düzgün, Emilio J. Mascort-Albea, Rocío Romero-Hernández
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0117
https://doi.org/10.56952/ARMA-2024-0117
Add To Cart
View Paper titled, Real-Time Prediction of Potential Hazard Area in Seville's During Underground Excavation with EPB
Open the PDF for Real-Time Prediction of Potential Hazard Area in Seville's During Underground Excavation with EPB in another window
Add to Citation Manager for Real-Time Prediction of Potential Hazard Area in Seville's During Underground Excavation with EPB
Proceedings Papers

Research on Prediction Methods of Mud Loss Risk Based on Different Seismic Attributes

Available to Purchase

Xing Fu, Renjun Xie, Changsuo Zhou, Xiaojian Wan, Yangjie Song, Xin Zhang, Yunhu Lu
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0187
https://doi.org/10.56952/ARMA-2024-0187
Add To Cart
View Paper titled, Research on Prediction Methods of Mud Loss Risk Based on Different Seismic Attributes
Open the PDF for Research on Prediction Methods of Mud Loss Risk Based on Different Seismic Attributes in another window
Add to Citation Manager for Research on Prediction Methods of Mud Loss Risk Based on Different Seismic Attributes
Proceedings Papers

Deep Learning for S-Wave Arrival Time Picking in Acoustic Emission Source Location Analysis

Available to Purchase

Q. Xiong, E. K. Johnson, C. S. Wu, J. C. Hampton
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0279
https://doi.org/10.56952/ARMA-2024-0279
Add To Cart
View Paper titled, Deep Learning for S-Wave Arrival Time Picking in Acoustic Emission Source Location Analysis
Open the PDF for Deep Learning for S-Wave Arrival Time Picking in Acoustic Emission Source Location Analysis in another window
Add to Citation Manager for Deep Learning for S-Wave Arrival Time Picking in Acoustic Emission Source Location Analysis
Proceedings Papers

Hyperparameter Tuning of an Artificial Neural Network (ANN) for Laboratory Acoustic Emission Source Location

Available to Purchase

Q. Xiong, E. K. Johnson, C. S. Wu, J. C. Hampton
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0277
https://doi.org/10.56952/ARMA-2024-0277
Add To Cart
View Paper titled, Hyperparameter Tuning of an Artificial Neural Network (ANN) for Laboratory Acoustic Emission Source Location
Open the PDF for Hyperparameter Tuning of an Artificial Neural Network (ANN) for Laboratory Acoustic Emission Source Location in another window
Add to Citation Manager for Hyperparameter Tuning of an Artificial Neural Network (ANN) for Laboratory Acoustic Emission Source Location
Proceedings Papers

An Autoencoder-Based Deep Learning Model for Enhancing Noise Characterization and Microseismic Event Detection in Underground Longwall Coal Mines Using Distributed Acoustic Sensing Monitoring

Available to Purchase

A. Tourei, E. R. Martin, A. T. Ankamah, J. A. Hole, D. J. A. Chambers
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0207
https://doi.org/10.56952/ARMA-2024-0207
Add To Cart
View Paper titled, An Autoencoder-Based Deep Learning Model for Enhancing Noise Characterization and Microseismic Event Detection in Underground Longwall Coal Mines Using Distributed Acoustic Sensing Monitoring
Open the PDF for An Autoencoder-Based Deep Learning Model for Enhancing Noise Characterization and Microseismic Event Detection in Underground Longwall Coal Mines Using Distributed Acoustic Sensing Monitoring in another window
Add to Citation Manager for An Autoencoder-Based Deep Learning Model for Enhancing Noise Characterization and Microseismic Event Detection in Underground Longwall Coal Mines Using Distributed Acoustic Sensing Monitoring
Proceedings Papers

Methodology for Constructing Three-Dimensional DEM Model of Rock Specimen from CT Scan

Available to Purchase

Changdi He, Brijes Mishra
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0261
https://doi.org/10.56952/ARMA-2024-0261
Add To Cart
View Paper titled, Methodology for Constructing Three-Dimensional DEM Model of Rock Specimen from CT Scan
Open the PDF for Methodology for Constructing Three-Dimensional DEM Model of Rock Specimen from CT Scan in another window
Add to Citation Manager for Methodology for Constructing Three-Dimensional DEM Model of Rock Specimen from CT Scan
Proceedings Papers

Seismic Data and Prediction of Mud Loss Risk Based on Physical Information Constraints

Available to Purchase

Renjun Xie, Changsuo Zhou, Xing Fu, Xiaojian Wan, Yangjie Song, Xin Zhang, Yunhu Lu
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0186
https://doi.org/10.56952/ARMA-2024-0186
Add To Cart
View Paper titled, Seismic Data and Prediction of Mud Loss Risk Based on Physical Information Constraints
Open the PDF for Seismic Data and Prediction of Mud Loss Risk Based on Physical Information Constraints in another window
Add to Citation Manager for Seismic Data and Prediction of Mud Loss Risk Based on Physical Information Constraints
Proceedings Papers

Prediction of Formation Pressure Relief by Using Neural Network

Available to Purchase

Yanchao Li, Yanfang Gao, Shijie Shen, Dengke Li, Zupeng Chen, Xuelin Liang
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0331
https://doi.org/10.56952/ARMA-2024-0331
Add To Cart
View Paper titled, Prediction of Formation Pressure Relief by Using Neural Network
Open the PDF for Prediction of Formation Pressure Relief by Using Neural Network in another window
Add to Citation Manager for Prediction of Formation Pressure Relief by Using Neural Network
Proceedings Papers

A Training Experiment on the Cost and Benefit of Training U-Net for Laboratory Signal Processing

Available to Purchase

A Kong, C. Wang, Q. Lin, X. Qiquan, N. Opperman, C. Wu, E. P. Knippel, J. C. Hampton
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0288
https://doi.org/10.56952/ARMA-2024-0288
Add To Cart
View Paper titled, A Training Experiment on the Cost and Benefit of Training U-Net for Laboratory Signal Processing
Open the PDF for A Training Experiment on the Cost and Benefit of Training U-Net for Laboratory Signal Processing in another window
Add to Citation Manager for A Training Experiment on the Cost and Benefit of Training U-Net for Laboratory Signal Processing
Proceedings Papers

Evaluating the Data Augmentation on Acoustic Emission (AE) Signals for Training a Deep Neural Network

Available to Purchase

D. K. Kong, C. W. Wang, Q. Lin, Q. Xiong, C. S. Wu, E. P. Knippel, N. D. Opperman, J. C. Hampton
Paper presented at the 58th U.S. Rock Mechanics/Geomechanics Symposium, June 23–26, 2024
Paper Number: ARMA-2024-0289
https://doi.org/10.56952/ARMA-2024-0289
Add To Cart
View Paper titled, Evaluating the Data Augmentation on Acoustic Emission (AE) Signals for Training a Deep Neural Network
Open the PDF for Evaluating the Data Augmentation on Acoustic Emission (AE) Signals for Training a Deep Neural Network in another window
Add to Citation Manager for Evaluating the Data Augmentation on Acoustic Emission (AE) Signals for Training a Deep Neural Network

Product(s) added to cart

Go to Cart Continue Browsing
Close Modal