Prediction of Ground Properties Using Machine Learning Techniques.
- Prediction of Ground Properties Using Machine Learning Techniques. – References till 2009
- An empirical study on the effect of spatial variability of block-type cement-treated ground on the bearing capacity of foundation under inclined load – References Till 2010
- Artificial Intelligence in Geotechnical Engineering: Applications, Modeling Aspects, and Future Predictions. – References till 2010
- A critical review on the Automated Methods and Systems for Construction Planning and Scheduling. – References till 2011
- Challenges in geotechnical design revealed by reliability assessment: Review and future perspectives – References till 2011
- Modelling pile capacity and load-settlement behaviour of piles embedded in sand & mixed soils using artificial intelligence. – References till 2012
- A critical review of artificial intelligence applications in TBM, NATM & NMT Tunnels.- References till 2012
- Prediction of maximum surface settlement caused by earth pressure balance (EPB) shield tunneling with ANN methods.-References till 2013
- Modeling load-settlement behavior of driven piles embedded in cohesive soils using artificial neural networks. REFERENCES TILL 2013
- A case study on the Predictive and Prescriptive Analytics in Underground space structures. RWFERENCES TILL 2014
- Genetic programming for modelling of soil – structure interactions. REFERENCES TILL 2014
- An empirical study on the methods and Instruments for Automated Geotechnical Monitoring. REFERENCES TILP 2015
- Modelling soil behaviour in uniaxial strain conditions by neural networks. REFERENCES TILL 2015
- Applications of Artificial Intelligence and Machine Learning in Geotechnical Engineering. REFERENCES TILL 2016
- Automation of the Digital Information Workflow in the Geotechnical Design Process. REFERENCES TILL 2016
- Emerging technologies and the future of geotechnical instrumentation. REFERENCES TILL 2017
- Automatic Damage Detection using Machine Learning and Deep Learning. REFERENCES TILL 2017
- Automation and Artificial Intelligence in Construction and Management of Civil Infrastructure. REFERENCES TILL 2018
- A Machine Learning Framework for Predicting Displacements due to Deep excavations and Tunnels. REFERENCES TILL 2018
- Automation in Civil Engineering Design in Assessing Underground Space Energy Efficiency. REFERENCES TILL 2019
- Forecasting displacement of underground caverns using machine learning techniques. REFERENCES TILL 2019
- A Comparative Analysis of Utilization of Advanced Techniques for Ground Improvements in weak soils. REFERENCES TILL 2020
- Accident prediction in construction using hybrid wavelet-machine learning. REFERENCES TILL 2020
- An empirical study on the best prediction model of water inflow into drill and blast tunnels among several machine learning techniques. REFERENCES TILL 2018
- State-of-the-art review of some artificial intelligence applications in Deep Excavations. REFERENCES TILL 2020
- Machine Learning Applications in Civil Engineering: An empirical study. REFERENCES TILL 2021
- An empirical study on the benefits of civil systems connectivity and automation – a discussion in the context of Metro transport. REFERENCES TILL 2017
- Machine learning aids earthquake risk prediction. REFERENCES TILL 2018
- Modelling soil behaviour in uniaxial strain conditions by neural networks. REFERENCES TILL 2017
- Machine Learning Applications for Site Characterization Based on CPT Data. REFERENCES TILL 2016
- Reducing the risks in geotechnical engineering using artificial intelligence techniques. REFERENCES TILL 2021
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