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Full-Text Articles in Engineering
Integrating Deep Learning And Hydrodynamic Modeling To Improve The Great Lakes Forecast, Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang
Integrating Deep Learning And Hydrodynamic Modeling To Improve The Great Lakes Forecast, Pengfei Xue, Aditya Wagh, Gangfeng Ma, Yilin Wang, Yongchao Yang, Tao Liu, Chenfu Huang
Michigan Tech Publications
The Laurentian Great Lakes, one of the world’s largest surface freshwater systems, pose a modeling challenge in seasonal forecast and climate projection. While physics-based hydrodynamic modeling is a fundamental approach, improving the forecast accuracy remains critical. In recent years, machine learning (ML) has quickly emerged in geoscience applications, but its application to the Great Lakes hydrodynamic prediction is still in its early stages. This work is the first one to explore a deep learning approach to predicting spatiotemporal distributions of the lake surface temperature (LST) in the Great Lakes. Our study shows that the Long Short-Term Memory (LSTM) neural network, …
Long Short-Term Memory Based Subsurface Drainage Control For Rainfall-Induced Landslide Prevention, Aynaz Biniyaz, Behnam Azmoon, Ye Sun, Zhen Liu
Long Short-Term Memory Based Subsurface Drainage Control For Rainfall-Induced Landslide Prevention, Aynaz Biniyaz, Behnam Azmoon, Ye Sun, Zhen Liu
Michigan Tech Publications
Subsurface drainage has been widely accepted to mitigate the hazard of landslides in areas prone to flooding. Specifically, the use of drainage wells with pumping systems has been recognized as an effective short-term solution to lower the groundwater table. However, this method has not been well considered for long-term purposes due to potentially high labor costs. This study aims to investigate the idea of an autonomous pumping system for subsurface drainage by leveraging con-ventional geotechnical engineering solutions and a deep learning technique—Long-Short Term Memory (LSTM)—to establish a geotechnical cyber-physical system for rainfall-induced landslide prevention. For this purpose, a typical soil …
Research And Applications Of Artificial Neural Network In Pavement Engineering: A State-Of-The-Art Review, Xu Yang, Jinchao Guan, Ling Ding, Zhanping You, Vincent C.S. Lee, Mohd Rosli Mohd Hasan, Xiaoyun Cheng
Research And Applications Of Artificial Neural Network In Pavement Engineering: A State-Of-The-Art Review, Xu Yang, Jinchao Guan, Ling Ding, Zhanping You, Vincent C.S. Lee, Mohd Rosli Mohd Hasan, Xiaoyun Cheng
Michigan Tech Publications
Given the great advancements in soft computing and data science, artificial neural network (ANN) has been explored and applied to handle complicated problems in the field of pavement engineering. This study conducted a state-of-the-art review for surveying the recent progress of ANN application at different stages of pavement engineering, including pavement design, construction, inspection and monitoring, and maintenance. This study focused on the papers published over the last three decades, especially the studies conducted since 2013. Through literature retrieval, a total of 683 papers in this field were identified, among which 143 papers were selected for an in-depth review. The …
Evaluation Of Deep Learning Against Conventional Limit Equilibrium Methods For Slope Stability Analysis, Behnam Azmoon, Aynaz Biniyaz, Zhen (Leo) Liu
Evaluation Of Deep Learning Against Conventional Limit Equilibrium Methods For Slope Stability Analysis, Behnam Azmoon, Aynaz Biniyaz, Zhen (Leo) Liu
Michigan Tech Publications
This paper presents a comparison study between methods of deep learning as a new cat-egory of slope stability analysis, built upon the recent advances in artificial intelligence and conventional limit equilibrium analysis methods. For this purpose, computer code was developed to cal-culate the factor of safety (FS) using four limit equilibrium methods: Bishop’s simplified method, the Fellenius method, Janbu’s simplified method, and Janbu’s corrected method. The code was ver-ified against Slide2 in RocScience. Subsequently, the average FS values were used to approximate the “true” FS of the slopes for labeling the images for deep learning. Using this code, a comprehensive …