4.7 Article

Dynamic prediction models of rock quality designation in tunneling projects

Related references

Note: Only part of the references are listed.
Article Automation & Control Systems

A study on leading machine learning techniques for high order fuzzy time series forecasting

Sibarama Panigrahi et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2020)

Article Automation & Control Systems

Power prediction for electric vehicles using online machine learning

Stephan Rhode et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2020)

Review Automation & Control Systems

The application of machine learning techniques for driving behavior analysis: A conceptual framework and a systematic literature review

Zouhair Elamrani Abou Elassad et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2020)

Article Automation & Control Systems

Dynamic Bayesian network for robust latent variable modeling and fault classification

Junhua Zheng et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2020)

Article Construction & Building Technology

Decision-making in tunneling using artificial intelligence tools

Arsalan Mahmoodzadeh et al.

TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY (2020)

Article Construction & Building Technology

Forecasting maximum surface settlement caused by urban tunneling

Arsalan Mahmoodzadeh et al.

AUTOMATION IN CONSTRUCTION (2020)

Article Multidisciplinary Sciences

Gaussian Process Regression Technique to Estimate the Pile Bearing Capacity

Ehsan Momeni et al.

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING (2020)

Article Multidisciplinary Sciences

Predicting Convergence Rate of Namaklan Twin Tunnels Using Machine Learning Methods

Mehdi Torabi-Kaveh et al.

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING (2020)

Article Engineering, Environmental

Predicting tunnel boring machine performance through a new model based on the group method of data handling

Mohammadreza Koopialipoor et al.

BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2019)

Article Environmental Sciences

Extreme learning machine-based prediction of daily water temperature for rivers

Senlin Zhu et al.

ENVIRONMENTAL EARTH SCIENCES (2019)

Article Automation & Control Systems

Railway track fastener defect detection based on image processing and deep learning techniques: A comparative study

Xiukun Wei et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2019)

Article Construction & Building Technology

Updating ground conditions and time-cost scatter-gram in tunnels during excavation

Arsalan Mahmoodzadeh et al.

AUTOMATION IN CONSTRUCTION (2019)

Article Construction & Building Technology

Dynamic prediction for attitude and position in shield tunneling: A deep learning method

Cheng Zhou et al.

AUTOMATION IN CONSTRUCTION (2019)

Article Environmental Sciences

Land subsidence susceptibility assessment using random forest machine learning algorithm

Majid Mohammady et al.

ENVIRONMENTAL EARTH SCIENCES (2019)

Article Chemistry, Multidisciplinary

Supervised Machine Learning Techniques to the Prediction of Tunnel Boring Machine Penetration Rate

Hai Xu et al.

APPLIED SCIENCES-BASEL (2019)

Article Automation & Control Systems

Multiscale Gaussian process regression-based generalized likelihood ratio test for fault detection in water distribution networks

R. Fazai et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2019)

Article Automation & Control Systems

Performance enhancing techniques for deep learning models in time series forecasting

Xing Fang et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2019)

Article Chemistry, Multidisciplinary

A Gene Expression Programming Model for Predicting Tunnel Convergence

Mohsen Hajihassani et al.

APPLIED SCIENCES-BASEL (2019)

Article Multidisciplinary Sciences

Prediction of Uniaxial Compressive Strength of Different Quarried Rocks Using Metaheuristic Algorithm

Reza Asheghi et al.

ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING (2019)

Article Engineering, Geological

Application of several optimization techniques for estimating TBM advance rate in granitic rocks

Danial Jahed Armaghani et al.

JOURNAL OF ROCK MECHANICS AND GEOTECHNICAL ENGINEERING (2019)

Article Engineering, Environmental

Model tree approach for predicting uniaxial compressive strength and Young's modulus of carbonate rocks

Ebrahim Ghasemi et al.

BULLETIN OF ENGINEERING GEOLOGY AND THE ENVIRONMENT (2018)

Article Automation & Control Systems

Adaptive sequential strategy for risk estimation of engineering systems using Gaussian process regression active learning

Hamoon Azizsoltani et al.

ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE (2018)

Article Environmental Sciences

Digital soil mapping in a Himalayan watershed using remote sensing and terrain parameters employing artificial neural network model

Justin George Kalambukattu et al.

ENVIRONMENTAL EARTH SCIENCES (2018)

Article Computer Science, Artificial Intelligence

Variable selection and prediction of uniaxial compressive strength and modulus of elasticity by random forest

S. S. Matin et al.

APPLIED SOFT COMPUTING (2018)

Article Engineering, Geological

Prediction of Uniaxial Compressive Strength of Some Sedimentary Rocks by Fuzzy and Regression Models

Mojtaba Heidari et al.

GEOTECHNICAL AND GEOLOGICAL ENGINEERING (2018)

Article Construction & Building Technology

Gaussian process model of water inflow prediction in tunnel construction and its engineering applications

Shu-cai Li et al.

TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY (2017)

Article Construction & Building Technology

Development of hybrid intelligent models for predicting TBM penetration rate in hard rock condition

Danial Jahed Armaghani et al.

TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY (2017)

Proceedings Paper Mining & Mineral Processing

An ANN Approach for the Prediction of Uniaxial Compressive Strength, of Some Sedimentary and Igneous Rocks in Eastern KwaZulu-Natal

Maria Ferentinou et al.

ISRM EUROPEAN ROCK MECHANICS SYMPOSIUM EUROCK 2017 (2017)

Article Engineering, Multidisciplinary

Regression Models and Fuzzy Logic Prediction of TBM Penetration Rate

Vu Trieu Minh et al.

OPEN ENGINEERING (2017)

Article Geosciences, Multidisciplinary

Prediction of the strength and elasticity modulus of granite through an expert artificial neural network

Danial Jahed Armaghani et al.

ARABIAN JOURNAL OF GEOSCIENCES (2016)

Article Engineering, Geological

Prediction of the uniaxial compressive strength of sandstone using various modeling techniques

Danial Jahed Armaghani et al.

INTERNATIONAL JOURNAL OF ROCK MECHANICS AND MINING SCIENCES (2016)

Article Engineering, Multidisciplinary

Prediction of compressive strength and elastic modulus of carbonate rocks

N. Madhubabu et al.

MEASUREMENT (2016)

Article Construction & Building Technology

Application of non-linear regression analysis and artificial intelligence algorithms for performance prediction of hard rock TBMs

Alireza Salimi et al.

TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY (2016)

Article Engineering, Geological

Probabilistic prediction of expected ground condition and construction time and costs in road tunnels

A. Mahmoodzadeh et al.

JOURNAL OF ROCK MECHANICS AND GEOTECHNICAL ENGINEERING (2016)

Article Engineering, Geological

Estimation of tunnelling-induced settlement by modern intelligent methods

Kaveh Ahangari et al.

SOILS AND FOUNDATIONS (2015)

Article Engineering, Multidisciplinary

Displacement Prediction of Tunnel Surrounding Rock: A Comparison of Support Vector Machine and Artificial Neural Network

Qingdong Wu et al.

MATHEMATICAL PROBLEMS IN ENGINEERING (2014)

Article Construction & Building Technology

Probabilistic estimation of ground condition and construction cost for mountain tunnels

Zhenchang Guan et al.

TUNNELLING AND UNDERGROUND SPACE TECHNOLOGY (2014)

Article Geosciences, Multidisciplinary

Combining Electrical Resistivity Tomography and Ground Penetrating Radar to study geological structuring of karst Unsaturated Zone

Simon D. Carriere et al.

JOURNAL OF APPLIED GEOPHYSICS (2013)

Article Geosciences, Multidisciplinary

Prediction of rock burst classification using the technique of cloud models with attribution weight

Zaobao Liu et al.

NATURAL HAZARDS (2013)