A platform for research: civil engineering, architecture and urbanism
A platform for research: civil engineering, architecture and urbanism
Application of Artificial Neural Network in Predicting the Dispersibility of Soil
Under the action of seepage or surface erosion, earth dams, canal foundations, subgrades and embankments filled with dispersive soils can easily cause piping, caves, gullies and other damages and even cause accidents in civil engineering and hydraulic engineering. Thus, how to correctly distinguish the dispersibility of soils is concerned by soils engineers all the time. In this study, the artificial neural network model was developed to recognize dispersive soils by using TensorFlow which is an open-source library of Python. The data samples were from 11 water conservancy projects located in west of China. The results show that the artificial neural network model has a great effect in predicting the dispersibility of soil. A combination of artificial neural network and Python is applicable to solve complex, fuzzy and highly nonlinear problems in civil engineering and hydraulic engineering, which is also one of the important trends in the future study.
Application of Artificial Neural Network in Predicting the Dispersibility of Soil
Under the action of seepage or surface erosion, earth dams, canal foundations, subgrades and embankments filled with dispersive soils can easily cause piping, caves, gullies and other damages and even cause accidents in civil engineering and hydraulic engineering. Thus, how to correctly distinguish the dispersibility of soils is concerned by soils engineers all the time. In this study, the artificial neural network model was developed to recognize dispersive soils by using TensorFlow which is an open-source library of Python. The data samples were from 11 water conservancy projects located in west of China. The results show that the artificial neural network model has a great effect in predicting the dispersibility of soil. A combination of artificial neural network and Python is applicable to solve complex, fuzzy and highly nonlinear problems in civil engineering and hydraulic engineering, which is also one of the important trends in the future study.
Application of Artificial Neural Network in Predicting the Dispersibility of Soil
Iran J Sci Technol Trans Civ Eng
Zhang, Lu (author) / Du, Yu-Hang (author) / Yang, Xiu-Juan (author) / Fan, Heng-Hui (author)
2022-06-01
10 pages
Article (Journal)
Electronic Resource
English
Predicting Micropile Group Capacity in Soft Cohesive Soil by Artificial Neural Network
| Springer Verlag | 2024
Dispersibility of Carbon Nanotubes
| British Library Online Contents | 2007
Application of Artificial Neural Network(s) in Predicting Formwork Labour Productivity
| DOAJ | 2019
Research on Application of Artificial Neural Network in Predicting Mining Subsidence
| British Library Online Contents | 2002